{ "schemaVersion": "deck-intelligence.v1", "id": "019dd923-5ca1-7489-b638-e91d3b8478cc", "slug": "9fbedbfea0231cbe", "title": "AI Healthcare Errors", "subtitle": "McKinsey", "author": "McKinsey", "pageCount": 26, "kind": "consulting-deck", "orientation": "landscape", "aspectRatio": 1.333, "document": { "id": "019dd923-5ca1-7489-b638-e91d3b8478cc", "slug": "9fbedbfea0231cbe", "title": "AI Healthcare Errors", "rawTitle": "AI Healthcare Errors", "authorId": "McKinsey", "authorName": "McKinsey", "authorDisplay": "McKinsey", "kind": { "slug": "consulting-deck", "label": "Consulting deck" }, "sourceType": { "slug": "strategy_consulting", "label": "Strategy consulting" }, "fileName": "2017-AI-Healthcare-Errors.pdf", "sourceUrl": "https://www.bundesgesundheitsministerium.de/fileadmin/Dateien/3_Downloads/P/Patientensicherheit/WS3-2017/01_WS3_Henke_20170328_Using_AI_to_prevent_healthcare_errors_from_occuring.pdf", "sourceDate": "2017-03-29 00:00:00", "presentationDate": null, "ingestedAt": "2026-04-23 20:51:39+00", "status": "ready", "pageCount": 26, "orientation": "landscape", "aspectRatio": 1.333, "targetCompany": null, "targetTicker": null, "metadata": { "local_root": "/tmp/legacy-images/9fbedbfea0231cbe", "origin_corpus": "consulting" } }, "coverage": { "pageCount": 26, "pagesIndexed": 26, "pagesWithImages": 26, "pagesWithMetadata": 26, "imageCoveragePct": 100, "metadataCoveragePct": 100, "componentCount": 145, "chartCount": 13, "metricSlides": 13, "toolMatches": 13, "documentToolMatches": 0, "frameworkMatches": 12, "arcMatches": 1, "beatMatches": 3, "loopMatches": 2, "patternMatches": 0, "storymakersMatch": false, "scoreAvailable": true, "reviewAvailable": true, "activistThesisAvailable": false, "pitchdeckMetadataAvailable": false, "pitchdeckProfileAvailable": false }, "blocks": [], "matches": { "arcs": [ { "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "evidence": "The deck follows a problem-agitate-solution structure, presenting the problem of healthcare errors, agitating it by highlighting the consequences, and offering AI as a solution.", "isPrimary": true, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:07:17.122587+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "beats": [ { "to": 4, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 1, "name": "Problem (Identify pain)", "beatId": "408b877d-e516-4bcc-a74e-b47c048efe99", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Problem (Identify pain)", "slug": "problem-agitate-solution-problem-identify-pain", "status": "active", "canonId": "019dd9b8-0e78-74bb-b8f6-54348367a131", "version": 1, "description": null }, "evidence": "The deck starts by highlighting the problem of healthcare errors and their consequences.", "position": 0, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 0.8 }, { "to": 9, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 5, "name": "Agitate (Make it worse)", "beatId": "d51be049-4dec-43b6-a2f4-36ba79ee1b19", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Agitate (Make it worse)", "slug": "problem-agitate-solution-agitate-make-it-worse", "status": "active", "canonId": "019dd9b8-0f5a-71dd-bae7-8fadb0d09456", "version": 1, "description": null }, "evidence": "The deck presents various case studies and examples of errors and their consequences, making the problem worse.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "alignedBlockIds": null, "matchConfidence": 0.8 }, { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 18, "from": 18, "loop": { "name": "27_cost_of_inaction", "slug": "27-cost-of-inaction", "status": "active", "bestFor": "Urgent budget requests, compliance, risk mitigation", "canonId": "019dd956-70d1-7395-a15b-857ba858b394", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point", "description": "Quantify what happens if the audience does nothing", "familyLabel": null, "categoryName": "Urgency", "categorySlug": "urgency" }, "matchId": "7e5a1b2d-6045-4ae5-9071-3c7f16a0a952", "evidence": "The deck presents a slide on the significant further value at stake, highlighting the cost of inaction.", "position": 0, "objective": "Highlight the cost of inaction in healthcare error prevention", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.25806+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } }, { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null, "categoryName": "Vision", "categorySlug": "vision" }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "tools": [ { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "75cc0503-d101-4446-ae67-aa3945702269", "evidence": "The slide is targeted at explaining why machine learning is different, indicating an audience with some statistical background.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:57.746288+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "17a177bd-0a4a-4731-a4fc-de705efa601d", "evidence": "Medical imaging plays an important role in the early detection and diagnosis of breast cancer.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.195507+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "1c3c04ca-aa3a-4eb3-a65c-463d0591f387", "evidence": "Outperforms most other state-of-the-art CADx MRI diagnostic systems. Significantly reduces rate of false positives.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.23729+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "6d015149-53ef-40f4-bd90-aceb0e234502", "evidence": "Prediction models that incorporate longitudinal clinical data can capture non-linear disease progression in chronic hepatitis C.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.322427+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "5b0eabaa-4655-4795-af72-1438890f01f0", "evidence": "AUC scores for Linear regression (0.78), Random forest (0.79), and Boosting (0.79).", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.365357+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "566b1c17-6880-416a-ae8c-58ed9b39e96a", "evidence": "Cumulative % of total admissions captured", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.44948+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Before-After-Bridge", "slug": "before-after-bridge", "status": "active", "bestFor": null, "canonId": "019dd956-8604-7188-883f-42370288ad05", "version": 1, "bodyDocId": null, "description": "Narrative structure: Paint the before, show the after, explain the bridge", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "07e7ebf0-0d79-4f40-b376-14badd51e603", "evidence": "Up to 50% fewer FTEs in A&E; 40-50% shorter patient waiting time", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.534184+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "54e94461-f998-4eba-81f2-2b04137ec928", "evidence": "€15-20M saved in absenteeism costs; Root cause drivers of attrition by cohort/cluster; Tailored interventions based on individual risk lists", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.621362+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Waterfall chart", "slug": "waterfall-chart", "status": "active", "bestFor": null, "canonId": "e2799da3-725f-44a9-a093-570f1f388e64", "version": 1, "bodyDocId": null, "description": null, "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "8ea9cca8-3645-46a4-80cc-b3ec0e2a465f", "evidence": "Global Value created, $B", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:15:51.705042+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Comparison frame", "slug": "comparison-frame", "status": "active", "bestFor": null, "canonId": "019dd9e1-484b-7399-a4fc-d14644b99f93", "version": 1, "bodyDocId": null, "description": "Two or more states/subjects placed side by side to expose a gap.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "f055cc6e-9295-4eeb-96d7-7626ab9dc98e", "evidence": "Comparison of barriers across 12 categories for Location based data and Healthcare", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.789474+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Before-After-Bridge", "slug": "before-after-bridge", "status": "active", "bestFor": null, "canonId": "019dd956-8604-7188-883f-42370288ad05", "version": 1, "bodyDocId": null, "description": "Narrative structure: Paint the before, show the after, explain the bridge", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "a186e3a8-b93c-42aa-bff2-f43afd4d2bcd", "evidence": "From “spaghetti” architecture with redundant DWHs and staging areas and replicated data To all data into one repository and consolidation of all redundant DWHs and staging areas", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.957017+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "4d542a03-3a55-462f-86a3-c0497c085de3", "evidence": "The slide contains a numbered list with specific points.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:15:51.72328+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "e241661c-c763-4c10-ab30-d1cab1b197f9", "evidence": "The slide contains a numbered list with key take away messages.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:15:51.800306+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [ { "matchId": "b3167f45-b2b3-47f8-b953-9f0f1b234455", "evidence": "Situation-Approach-Impact structure", "framework": null, "confidence": 0.8, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 6, "frameworkName": "before-after-bridge" }, { "matchId": "35bdff90-0006-42d8-8e26-60fe32f8517f", "evidence": "The slide explicitly uses a 'Before' and 'After' comparison to demonstrate impact.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "before-after-bridge" }, { "matchId": "ab2100dd-ee98-4828-afe1-f2a6a98c3519", "evidence": "Diagram showing data sources feeding into a central patient record", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "frameworkName": "hub-spoke" }, { "matchId": "d06004eb-de21-4806-aa8f-a9069b77581f", "evidence": "The chart demonstrates a concentration of impact (admissions) within a small segment of the population (top 1%).", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:55.414+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "frameworkName": "pareto-principle-80-20" }, { "matchId": "c16444f5-f918-49c0-a7ac-aa75dbd49751", "evidence": "Contrasts the initial problem state with the post-intervention impact results.", "framework": null, "confidence": 0.85, "extraction": { "at": "2026-05-02 19:21:56.666+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "frameworkName": "before-after-framing" }, { "matchId": "bc607312-039b-409b-abdc-9a5cc3ce889c", "evidence": "Quantifies potential value creation across multiple levers.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "frameworkName": "impact_sizing" }, { "matchId": "4563ade7-45c3-4c23-b4d6-f1ffe5699609", "evidence": "The slide compares two sectors across a shared set of criteria.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:21:57.041+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "frameworkName": "comparison_table" }, { "matchId": "c12a2afc-ec5e-4b51-8235-10d9d56f9eeb", "evidence": "The slide explicitly contrasts a 'spaghetti' architecture with a 'Big Data lake' architecture.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "frameworkName": "before-after-framing" }, { "matchId": "284bccfd-1bfe-4c6a-9d2c-af935d498cf7", "evidence": "Overlapping circles used to categorize roles", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 23, "frameworkName": "venn-diagram" }, { "matchId": "b35ac261-c603-44d6-95b4-ce25686c426a", "evidence": "The slide uses a structured grid to compare four distinct organizational archetypes across two dimensions (Description and Evaluation).", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:22:03.522+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "frameworkName": "matrix-nxn" }, { "matchId": "25cbffe2-e766-4274-94bd-dee70061068b", "evidence": "Numbered list of key strategic questions", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:57.662+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "frameworkName": "list-presentation" }, { "matchId": "f9f68ffe-7910-4667-85aa-da10ddc492ac", "evidence": "The slide uses a numbered list to present key takeaways.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:57.619+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "frameworkName": "list-presentation" } ], "patterns": [] }, "storymakers": null, "score": { "backend": "codex", "scoredAt": "2026-05-02 11:13:13.379+00", "subScores": { "scqa_arc": 59, "action_titles": 72, "mece_structure": 54, "closing_strength": 66, "evidence_quality": 78, "clarity_of_thesis": 58, "production_quality": 68, "visual_storytelling": 74 }, "totalScore": 66, "coveragePct": 100, "explanations": { "scqa_arc": "There is a partial SCQA arc from ML context to healthcare opportunity to adoption enablers, but slides 5-18 mostly function as an analytical evidence dump before the complication and answer are fully sharpened.", "action_titles": "Many titles are insight-bearing, especially slide 7, \"Predictive maintenance at a coal fired power station helped to reduce mill downtime by >50%,\" but slides 2-3, 8, 18, 19, and 26 remain closer to labels.", "mece_structure": "The deck has a broad three-part agenda, but the use cases across slides 5-18 overlap across sectors and do not form a MECE map of healthcare errors, value pools, or implementation barriers.", "closing_strength": "Slides 25-26 provide next-step questions and key takeaways, but the ending lacks a specific recommendation, owner, sequencing, or decision request.", "evidence_quality": "Evidence is relatively strong, with quantified case examples, AUC comparisons, value estimates, charts, and footnotes across slides 7, 9-16, and 18.", "clarity_of_thesis": "The central idea that AI/ML can prevent healthcare errors is visible by slides 1-5, but it is framed as a topic and examples rather than a crisp declarative thesis.", "production_quality": "Production quality is professional and consistent, but repeated agenda slides, dense layouts, some label titles, and minor wording issues such as slide 23 reduce polish.", "visual_storytelling": "The deck usually pairs messages with appropriate tools such as heatmaps on slides 4-5, charts on slides 10-15, and frameworks on slides 21-24, though several slides are overcrowded." }, "slidesAnalyzed": 26 }, "review": { "backend": null, "verdict": "A well-evidenced analytical case-study tour with strong mid-deck action titles, but it lacks the SCQA opener and synthesis closer needed to work as a Storymakers exemplar — use slides 9, 15 and 16 for teaching declarative titles, not the deck's overall arc.", "reviewedAt": "2026-04-25 02:29:03+00", "slidesSeen": 26, "suggestions": [ "Replace one of the three agenda slides with an SCQA opener that quantifies preventable healthcare errors and states the thesis ('AI can prevent X% of Y errors — here's how') in the first 3 pages", "Rename the section dividers from 'Agenda for today' to the actual pillar names (e.g. 'Why ML is different', 'Where it works in healthcare', 'How to industrialize it') so the MECE structure is visible", "Add a synthesis slide after p.17 that rolls the eight case studies into 2–3 patterns (e.g. diagnostic accuracy, ops efficiency, cost savings) before pivoting to barriers (p.19)", "Rewrite p.26 from 'Key take away messages' into a declarative recommendation title with a concrete next step and owner" ], "closingScore": 50, "openingScore": 40, "topStrengths": [ "Strong action titles in the analytical core (p.9, p.15, p.16) that lead with the number and the so-what", "Rich evidence base: ~10 case studies with AUC/accuracy figures (p.10 0.76, p.11 0.86, p.13 0.962, p.14 0.79) give the deck quantitative credibility", "Cross-industry analogues (football p.5, telecom p.6, power p.7) before the healthcare cases is a smart 'why now' move" ], "topWeaknesses": [ "No SCQA opener — the title promises 'preventing healthcare errors' but no slide in pp.1–8 sizes the error problem or names the Question", "Three identical 'Agenda for today' slides (p.2, p.3, p.8, p.20) waste prime real estate and signal pillars without ever labeling them", "Closing is a duplicate: p.25 reuses the p.21 divider title verbatim and p.26 is a topic label, so the deck ends without a crisp recommendation or ask", "Case studies p.10–p.17 read as a list rather than a build — no synthesis slide answers 'so across these eight proofs, what should the reader do?'" ], "narrativeScore": 55, "pillarCritique": "Three 'Agenda for today' slides (p.2/3, p.8, p.20) act as section dividers, implying a 3-pillar MECE structure, but the pillars are never named — the reader has to infer them from the case dump that follows each divider.", "closingCritique": "p.25 ('Advanced analytics capabilities and change management are key…') is a verbatim repeat of the p.21 divider, and p.26 'Key take away messages' is a label, not a memorable close or call to action. There is a recommendation slot but no sharp ask.", "openingCritique": "The first five slides burn three pages on cover/agenda/agenda, then open with a generic explainer ('Why is machine learning different?', p.4) and a football-injury case (p.5) — neither establishes stakes for healthcare errors, the title's promise. The thesis is never stated up front.", "extractionSeconds": 60.70187, "narrativeCritique": "The deck has a loose three-act shape (why ML matters → cross-industry & healthcare cases → enablers/next steps) but no real Complication: it never names the patient-safety problem the title promises, jumping straight from 'Why is ML different?' (p.4) into a parade of case studies. Resolution at p.25–26 restates capabilities rather than resolving a thesis arc.", "titleQualityScore": 62, "titleQualityCritique": "Mid-deck titles are genuinely declarative and metric-bearing ('US healthcare has seen increased adoption but only captured ~10% of 2011 value estimate', p.9; 'Tracking hospital operations in real-time allows automation, reducing A&E headcount by up to 50%…', p.16), but openers and closers regress to topic labels ('Why is machine learning different?' p.4; 'Key take away messages' p.26)." }, "activistThesis": null, "pitchdeck": { "metadata": null, "profile": null }, "slides": [ { "page": 1, "type": "setup", "function": "front_matter", "imagePath": "https://imgproxy.kitesheet.com/bA_FcXkLiKaV1z2fcnmcbEkLzgWhRmUOUZJ6l3qXG50/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy85ZmJlZGJmZWEwMjMxY2JlL3AwMDEuanBn", "rawType": "cover", "block": null, "metadata": { "slideType": "cover", "slideTypeCanon": { "name": "Cover", "slug": "cover", "status": "active", "canonId": "019de52d-05f2-729d-9f93-e0504f0a2410", "version": 1, "description": null }, "function": "front_matter", "functionCanon": { "name": "Front matter", "slug": "front_matter", "status": "active", "canonId": "019de52d-133d-73f0-9e26-201eda96b098", "version": 1, "description": null }, "density": "sparse", "densityScore": 20, "componentCount": 4, "textChars": 280, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:52.314+00", "seconds": 2.297, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/1", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-1", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.05, "w": 0.4, "x": 0.25, "y": 0.93 }, "kind": "disclaimer", "text": "CONFIDENTIAL AND PROPRIETARY. Any use of this material without specific permission of McKinsey & Company is strictly prohibited", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.314+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ab466f2c-24ff-4580-b57c-90b5fe84282e", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.25, "y": 0.53 }, "kind": "paragraph", "text": "Presentation | 29th March 2017", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.314+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6f149a63-15c9-4340-ae92-b942fe58793a", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.5, "x": 0.25, "y": 0.46 }, "kind": "paragraph", "text": "SECOND GLOBAL MINISTERIAL SUMMIT ON PATIENT SAFETY", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.314+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e02cc78b-413e-44d3-b03a-4c0d867b4c15", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.65, "x": 0.25, "y": 0.22 }, "kind": "title", "text": "Using Artificial Intelligence to prevent healthcare errors from occurring", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.314+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "aaea2658-88fa-43ed-b153-a6d198b48eb7", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 1, "name": "Problem (Identify pain)", "beatId": "408b877d-e516-4bcc-a74e-b47c048efe99", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Problem (Identify pain)", "slug": "problem-agitate-solution-problem-identify-pain", "status": "active", "canonId": "019dd9b8-0e78-74bb-b8f6-54348367a131", "version": 1, "description": null }, "evidence": "The deck starts by highlighting the problem of healthcare errors and their consequences.", "position": 0, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "thumbSrc": "https://imgproxy.kitesheet.com/3w_j4eOy3onGy5MDdzFt3WajlxbtOYENoRttpC3FtEQ/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy85ZmJlZGJmZWEwMjMxY2JlL3AwMDEuanBn", "imagePathAlt": "https://imgproxy.kitesheet.com/PVhbD_KyhlVGvd7_HA9MxC7UstzTg9zr56e85nAaTfs/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy85ZmJlZGJmZWEwMjMxY2JlL3AwMDEucG5n", "thumbSrcAlt": "https://imgproxy.kitesheet.com/rBpWfD2kt2TG2WiLUTwGS1UorfZ0cv7RtVHTO86RAhM/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy85ZmJlZGJmZWEwMjMxY2JlL3AwMDEucG5n" }, { "page": 2, "type": "setup", "function": "summarize", "rawType": "agenda", "block": null, "metadata": { "slideType": "agenda", "slideTypeCanon": { "name": "Agenda", "slug": "agenda", "status": "active", "canonId": "019de52d-061b-7470-b138-3ffa5e612cce", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "sparse", "densityScore": 12, "componentCount": 3, "textChars": 206, "nDataPoints": 0, "notes": null, "elementsJson": [ "numbered_list", "other" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:52.671+00", "seconds": 2.459, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/2", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-2", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.838, "w": 0.392, "x": 0.608, "y": 0.162 }, "kind": "image", "text": "Large question mark graphic", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.671+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "13289674-125c-4a72-be79-b778e2695c1c", "parentComponentId": null }, { "bbox": { "h": 0.53, "w": 0.54, "x": 0, "y": 0.238 }, "kind": "list", "text": "1. Why is Artificial Intelligence/Machine Learning different, and why now?\n2. Where is the opportunity in patient safety/patient care?\n3. How can we enable change?", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.671+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "07c6ad7c-d165-4cb0-a9aa-5e5587ec45e4", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.23, "x": 0.01, "y": 0.03 }, "kind": "title", "text": "Agenda for today", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.671+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1910da3d-a77a-48d8-8a0b-59cd9ac4d4fd", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 1, "name": "Problem (Identify pain)", "beatId": "408b877d-e516-4bcc-a74e-b47c048efe99", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Problem (Identify pain)", "slug": "problem-agitate-solution-problem-identify-pain", "status": "active", "canonId": "019dd9b8-0e78-74bb-b8f6-54348367a131", "version": 1, "description": null }, "evidence": "The deck starts by highlighting the problem of healthcare errors and their consequences.", "position": 0, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 3, "type": "setup", "function": "summarize", "rawType": "agenda", "block": null, "metadata": { "slideType": "agenda", "slideTypeCanon": { "name": "Agenda", "slug": "agenda", "status": "active", "canonId": "019de52d-061b-7470-b138-3ffa5e612cce", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "sparse", "densityScore": 12, "componentCount": 3, "textChars": 206, "nDataPoints": 0, "notes": null, "elementsJson": [ "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:52.727+00", "seconds": 2.004, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/3", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-3", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.712, "w": 0.392, "x": 0.608, "y": 0.152 }, "kind": "image", "text": "Large question mark graphic", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.727+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "91d25d42-8389-41ac-8986-c9d24ba9099d", "parentComponentId": null }, { "bbox": { "h": 0.48, "w": 0.54, "x": 0.01, "y": 0.238 }, "kind": "list", "text": "1. Why is Artificial Intelligence/Machine Learning different, and why now?\n2. Where is the opportunity in patient safety/patient care?\n3. How can we enable change?", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.727+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3cfa0c62-cb64-4c24-8177-52e206d11218", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.23, "x": 0.01, "y": 0.04 }, "kind": "title", "text": "Agenda for today", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:52.727+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3c37a262-ee95-4e9d-a7f2-b142636ef3cb", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 1, "name": "Problem (Identify pain)", "beatId": "408b877d-e516-4bcc-a74e-b47c048efe99", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Problem (Identify pain)", "slug": "problem-agitate-solution-problem-identify-pain", "status": "active", "canonId": "019dd9b8-0e78-74bb-b8f6-54348367a131", "version": 1, "description": null }, "evidence": "The deck starts by highlighting the problem of healthcare errors and their consequences.", "position": 0, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 4, "type": "analysis", "title": "Uses a heatmap visualization to contrast model fitting approaches.", "function": "diagnose", "rawType": "diagnosis", "block": null, "metadata": { "slideType": "diagnosis", "slideTypeCanon": { "name": "Diagnosis", "slug": "diagnosis", "status": "active", "canonId": "019de52d-0cd7-7212-898f-0464041ff8d8", "version": 1, "description": null }, "function": "diagnose", "functionCanon": { "name": "Diagnose", "slug": "diagnose", "status": "active", "canonId": "019de52d-1657-7223-acc5-7437d878c850", "version": 1, "description": null }, "density": "dense", "densityScore": 65, "componentCount": 8, "textChars": 667, "nDataPoints": 0, "notes": "Uses a heatmap visualization to contrast model fitting approaches.", "elementsJson": [ "headline_text", "heatmap", "paragraph" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:54.261+00", "seconds": 3.387, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/4", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-4", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "While ML algorithms are adapting themselves by spotting & recording patterns without clinging to any predetermined corset", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:36+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2bb-ba31adf49ad0", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.36, "y": 0.22 }, "kind": "chart", "text": "How Traditional stats sees it", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Heatmap", "slug": "heatmap", "status": "active", "canonId": "019de52d-00cd-71ee-bf36-233b7817c304", "version": 1, "description": null }, "framework": null }, "subkind": "heatmap", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5184fbf9-6cf4-4586-90df-b6463b4b8107", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.69, "y": 0.22 }, "kind": "chart", "text": "How Machine Learning sees it", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Heatmap", "slug": "heatmap", "status": "active", "canonId": "019de52d-00cd-71ee-bf36-233b7817c304", "version": 1, "description": null }, "framework": null }, "subkind": "heatmap", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "84529178-9f11-4b35-8634-ec26a829bb58", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.03, "y": 0.22 }, "kind": "chart", "text": "The actual phenomenon (real historical data)", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Heatmap", "slug": "heatmap", "status": "active", "canonId": "019de52d-00cd-71ee-bf36-233b7817c304", "version": 1, "description": null }, "framework": null }, "subkind": "heatmap", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "922f8737-9dfa-486b-887c-966e0eed2a5b", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.28, "x": 0.36, "y": 0.6 }, "kind": "paragraph", "text": "Traditional stats will fit a predetermined “shape” into the phenomenon (e.g. linear, quadratic, logarithmic models) – the square peg into the round hole!", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "39f34fb7-5fcd-4467-a3fb-777645940dc6", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.28, "x": 0.03, "y": 0.6 }, "kind": "paragraph", "text": "Real life phenomenon come in “all shapes and flavors” – showing patterns that are usually complex, non-linear and apparently disorganized", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "46d2c618-eb15-4faf-b417-be370ae9013e", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.28, "x": 0.69, "y": 0.6 }, "kind": "paragraph", "text": "While ML algorithms are adapting themselves by spotting & recording patterns without clinging to any predetermined corset", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6360e8bd-8f72-48e5-89d1-ab5302d80931", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.45, "x": 0.01, "y": 0.03 }, "kind": "title", "text": "Why is machine learning different?", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.261+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e0e52d5e-bccd-4d78-bd8d-0ef3d0599fa5", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "75cc0503-d101-4446-ae67-aa3945702269", "evidence": "The slide is targeted at explaining why machine learning is different, indicating an audience with some statistical background.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:57.746288+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 1, "name": "Problem (Identify pain)", "beatId": "408b877d-e516-4bcc-a74e-b47c048efe99", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Problem (Identify pain)", "slug": "problem-agitate-solution-problem-identify-pain", "status": "active", "canonId": "019dd9b8-0e78-74bb-b8f6-54348367a131", "version": 1, "description": null }, "evidence": "The deck starts by highlighting the problem of healthcare errors and their consequences.", "position": 0, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 5, "type": "evidence", "title": "The chart is a custom heatmap/matrix visualization showing player-match data.", "function": "quantify_impact", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "quantify_impact", "functionCanon": { "name": "Quantify impact", "slug": "quantify_impact", "status": "active", "canonId": "019de52d-1630-720d-b57d-fa7f76bebd8d", "version": 1, "description": null }, "density": "dense", "densityScore": 67, "componentCount": 8, "textChars": 572, "nDataPoints": 2, "notes": "The chart is a custom heatmap/matrix visualization showing player-match data.", "elementsJson": [ "headline_text", "heatmap", "big_number", "callout_box", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:56.89+00", "seconds": 5.766, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/5", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-5", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Improvement in accuracy of forecasting non-impact injuries: Forecast 170 of 184 non-impact muscle injuries across four squads and two years", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:25+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-108896d87361", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.75, "x": 0.05, "y": 0.15 }, "kind": "chart", "text": "Heatmap of player performance and match participation", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Heatmap", "slug": "heatmap", "status": "active", "canonId": "019de52d-00cd-71ee-bf36-233b7817c304", "version": 1, "description": null }, "framework": null }, "subkind": "heatmap", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.89+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "824c1a43-961d-495a-a062-bf661a703419", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.5, "x": 0.12, "y": 0.88 }, "kind": "legend", "text": "Above Average Performance, Average Performance, Below Average Performance, Duration on Pitch, Started Match, Substitute", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.89+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3d0a8e9d-4fb8-4e08-961c-ed9bd51f2249", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.1, "x": 0.83, "y": 0.17 }, "kind": "metric", "text": "90%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.89+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "051c20ba-52dc-43f2-993a-4ace0ce4dafe", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Accuracy of forecasting non-impact injuries: 90%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:25+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-17e45730d4dc", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.15, "x": 0.83, "y": 0.25 }, "kind": "paragraph", "text": "Improvement in accuracy of forecasting non-impact injuries: Forecast 170 of 184 non-impact muscle injuries across four squads and two years", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.89+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "eaa23d71-6366-4ab6-8dbc-89687640577b", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.02, "y": 0.97 }, "kind": "source-note", "text": "SOURCE: QuantumBlack", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.89+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "912e680e-60c4-4f1d-8f07-ce637ebc06c2", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.6, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Improving injury prediction in premiership football", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.89+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d5888f56-eb6a-48c8-8d84-7b923f0d4a8f", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Accuracy of forecasting non-impact injuries", "numberRaw": "90%", "numberKind": "percent", "actionTitle": "Improving injury prediction in premiership football", "calloutText": "Improvement in accuracy of forecasting non-impact injuries: Forecast 170 of 184 non-impact muscle injuries across four squads and two years", "numberScale": null, "numberValue": 90, "metricFamily": "other", "numberCurrency": null } ], "tools": [], "frameworks": [], "arcBeats": [ { "to": 9, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 5, "name": "Agitate (Make it worse)", "beatId": "d51be049-4dec-43b6-a2f4-36ba79ee1b19", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Agitate (Make it worse)", "slug": "problem-agitate-solution-agitate-make-it-worse", "status": "active", "canonId": "019dd9b8-0f5a-71dd-bae7-8fadb0d09456", "version": 1, "description": null }, "evidence": "The deck presents various case studies and examples of errors and their consequences, making the problem worse.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 6, "type": "evidence", "title": "Uses a Situation-Approach-Impact structure.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 69, "componentCount": 12, "textChars": 377, "nDataPoints": 3, "notes": "Uses a Situation-Approach-Impact structure.", "elementsJson": [ "headline_text", "paragraph", "big_number", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:54.373+00", "seconds": 3.208, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/6", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-6", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.04, "w": 0.35, "x": 0.57, "y": 0.81 }, "kind": "callout", "text": "Industry leading customer satisfaction score", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "99405a16-c79b-41ce-b9c6-c36f73c8a521", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.08, "x": 0.57, "y": 0.57 }, "kind": "metric", "text": "75%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4049fa7d-76ad-4eae-a08c-8e7f38a444fb", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.08, "x": 0.71, "y": 0.57 }, "kind": "metric", "text": "90%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e43a2e17-c87f-419e-839b-ae0304cb1c76", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.08, "x": 0.86, "y": 0.57 }, "kind": "metric", "text": "60%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f5694227-ec33-444a-97ac-ee7b5d9baba3", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Inbound service calls reduction: 60%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-77aff3cc754c", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.23, "x": 0.28, "y": 0.52 }, "kind": "paragraph", "text": "Approach: Full data capture of all network activities, customer and geolocation data to predict faults", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8bc50951-07d7-49b9-b470-a723aeb2d07f", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.23, "x": 0.025, "y": 0.52 }, "kind": "paragraph", "text": "Situation: Leading European telecoms and broadband provider needing to improve faults", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d7c92cf8-adf9-407f-8804-c8119cb58953", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.08, "x": 0.71, "y": 0.66 }, "kind": "subtitle", "text": "Predicted faults prevented", "attrs": null, "canon": { "kind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "82d821ee-2793-42e7-8f16-c6131385a3ce", "version": 1, "description": "Header-zone supporting text near the title (= ex body.description with bbox)." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1da97508-857b-4cd2-8165-6c7bf85165b1", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.08, "x": 0.86, "y": 0.66 }, "kind": "subtitle", "text": "Inbound service calls reduction", "attrs": null, "canon": { "kind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "82d821ee-2793-42e7-8f16-c6131385a3ce", "version": 1, "description": "Header-zone supporting text near the title (= ex body.description with bbox)." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7d4fb40f-1c41-40bf-bc28-f9e1d90b227f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.08, "x": 0.57, "y": 0.66 }, "kind": "subtitle", "text": "Faults predicted", "attrs": null, "canon": { "kind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "82d821ee-2793-42e7-8f16-c6131385a3ce", "version": 1, "description": "Header-zone supporting text near the title (= ex body.description with bbox)." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d4a70658-3dea-4548-8406-c56a2e9fe772", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.35, "x": 0.025, "y": 0.245 }, "kind": "title", "text": "Improving fault rate", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4a3cf50c-608d-4e28-b2ec-055fb00a8fd3", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.125, "x": 0.025, "y": 0.205 }, "kind": "title", "text": "Telecoms", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e9903124-fb32-4ec4-a453-02debcb8ef58", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Inbound service calls reduction", "numberRaw": "60%", "numberKind": "percent", "actionTitle": "Improving fault rate", "calloutText": "Industry leading customer satisfaction score", "numberScale": null, "numberValue": 60, "metricFamily": "other", "numberCurrency": null } ], "tools": [], "frameworks": [ { "matchId": "b3167f45-b2b3-47f8-b953-9f0f1b234455", "evidence": "Situation-Approach-Impact structure", "framework": null, "confidence": 0.8, "extraction": { "at": "2026-05-02 19:21:54.373+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 6, "frameworkName": "before-after-bridge" } ], "arcBeats": [ { "to": 9, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 5, "name": "Agitate (Make it worse)", "beatId": "d51be049-4dec-43b6-a2f4-36ba79ee1b19", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Agitate (Make it worse)", "slug": "problem-agitate-solution-agitate-make-it-worse", "status": "active", "canonId": "019dd9b8-0f5a-71dd-bae7-8fadb0d09456", "version": 1, "description": null }, "evidence": "The deck presents various case studies and examples of errors and their consequences, making the problem worse.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 7, "type": "evidence", "title": "Uses a classic Situation-Approach-Impact structure.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 65, "componentCount": 7, "textChars": 726, "nDataPoints": 5, "notes": "Uses a classic Situation-Approach-Impact structure.", "elementsJson": [ "headline_text", "bullet_list", "process_diagram", "bar_chart_vertical", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:54.243+00", "seconds": 2.763, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/7", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-7", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Model predicts failure 3 months in advance with >75% accuracy", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-6ecf4c9afbf6", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.35, "x": 0.58, "y": 0.55 }, "kind": "chart", "text": "Impact: Model predicts failure 3 months in advance with >75% accuracy; Down time reduced by >50%", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "28f93ab5-1586-4c13-9f9e-008a8d6649c2", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "53eb36b6-be23-43a7-9520-7cb231b91e11", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.25, "x": 0.05, "y": 0.55 }, "kind": "list", "text": "Situation: Station was suffering from low availability, unplanned maintenance was >3x the global average; Three components found to be key drivers of failure; Goal to reduce unplanned losses due to mill failures", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7f82d448-0c6a-41a1-acc1-395237265009", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.25, "x": 0.3, "y": 0.55 }, "kind": "list", "text": "Approach: Collected data 7 different data bases and logs; Identified key failures and validated failure events; Used machine learning to define and predict failures; Developed user interface to plan maintenance on time and implemented to shop floor", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Timeline item", "slug": "timeline-item", "status": "active", "canonId": "019de52c-fd0e-74ce-9443-440fbd8c23b4", "version": 1, "description": null }, "framework": null }, "subkind": "timeline-item", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "654e31b8-5932-4f6f-a486-da7ceb6784fa", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "mill downtime: >50%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-70c29b929404", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.45, "x": 0.05, "y": 0.25 }, "kind": "title", "text": "Predictive maintenance at a coal fired power station helped to reduce mill downtime by >50%", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "aba4f9b3-f06e-4f6e-a08d-cf88143f232f", "parentComponentId": null } ], "metrics": [ { "metricRaw": "mill downtime", "numberRaw": ">50%", "numberKind": "percent", "actionTitle": "Predictive maintenance at a coal fired power station helped to reduce mill downtime by >50%", "calloutText": "Model predicts failure 3 months in advance with >75% accuracy", "numberScale": null, "numberValue": 50, "metricFamily": "other", "numberCurrency": null } ], "tools": [], "frameworks": [ { "matchId": "35bdff90-0006-42d8-8e26-60fe32f8517f", "evidence": "The slide explicitly uses a 'Before' and 'After' comparison to demonstrate impact.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:54.243+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "before-after-bridge" } ], "arcBeats": [ { "to": 9, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 5, "name": "Agitate (Make it worse)", "beatId": "d51be049-4dec-43b6-a2f4-36ba79ee1b19", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Agitate (Make it worse)", "slug": "problem-agitate-solution-agitate-make-it-worse", "status": "active", "canonId": "019dd9b8-0f5a-71dd-bae7-8fadb0d09456", "version": 1, "description": null }, "evidence": "The deck presents various case studies and examples of errors and their consequences, making the problem worse.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 8, "type": "setup", "function": "summarize", "rawType": "agenda", "block": null, "metadata": { "slideType": "agenda", "slideTypeCanon": { "name": "Agenda", "slug": "agenda", "status": "active", "canonId": "019de52d-061b-7470-b138-3ffa5e612cce", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "sparse", "densityScore": 12, "componentCount": 3, "textChars": 206, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:22:11.525+00", "seconds": 20.027, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/8", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-8", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.8, "w": 0.35, "x": 0.6, "y": 0.15 }, "kind": "image", "text": "Large question mark graphic", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:11.525+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "586fac54-ff8d-4fc4-b62f-3b42832ecaaa", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.54, "x": 0.01, "y": 0.24 }, "kind": "list", "text": "1. Why is Artificial Intelligence/Machine Learning different, and why now?\n2. Where is the opportunity in patient safety/patient care?\n3. How can we enable change?", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:11.525+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d52597c6-dd5f-46a1-8f21-a06994f73aee", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.23, "x": 0.01, "y": 0.04 }, "kind": "title", "text": "Agenda for today", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:11.525+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e2ba71ea-c1f1-4e87-8245-94e952493fea", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 9, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 5, "name": "Agitate (Make it worse)", "beatId": "d51be049-4dec-43b6-a2f4-36ba79ee1b19", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Agitate (Make it worse)", "slug": "problem-agitate-solution-agitate-make-it-worse", "status": "active", "canonId": "019dd9b8-0f5a-71dd-bae7-8fadb0d09456", "version": 1, "description": null }, "evidence": "The deck presents various case studies and examples of errors and their consequences, making the problem worse.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 9, "type": "analysis", "title": "The slide uses a waterfall-like structure to show the gap between potential and realized value.", "function": "quantify_impact", "rawType": "data_table", "block": null, "metadata": { "slideType": "data_table", "slideTypeCanon": { "name": "Data table", "slug": "data_table", "status": "active", "canonId": "019de52d-0bbd-71b9-9918-417f904abbf8", "version": 1, "description": null }, "function": "quantify_impact", "functionCanon": { "name": "Quantify impact", "slug": "quantify_impact", "status": "active", "canonId": "019de52d-1630-720d-b57d-fa7f76bebd8d", "version": 1, "description": null }, "density": "dense", "densityScore": 61, "componentCount": 6, "textChars": 824, "nDataPoints": 15, "notes": "The slide uses a waterfall-like structure to show the gap between potential and realized value.", "elementsJson": [ "headline_text", "data_table", "callout_box", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:54.341+00", "seconds": 2.574, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/9", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-9", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.6, "w": 0.16, "x": 0.82, "y": 0.25 }, "kind": "callout", "text": "Major changes in industry incentives brought about by the ACA and rapid uptake of EMRs from ~30% in 2011 to 90+% today has contributed to general opening of healthcare data. Slow regulatory processes and monopolistic and segregated industry structure has resulted in only ~10% progress toward realizing BDAA value from 2011", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.341+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e57e14d5-722c-4595-9a8c-dca36271b2c9", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Slow regulatory processes and monopolistic and segregated industry structure has resulted in only ~10% progress toward realizing BDAA value from 2011", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:25+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-50ee3c53c625", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Value potential realized: ~10%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:25+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-561d3d96aa00", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.95 }, "kind": "source-note", "text": "SOURCE: Expert interviews; industry surveys on HIT adoption; McKinsey Global Institute analysis", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.341+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4f2aa0e5-3574-4b73-a24b-0a71b220003e", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.8, "x": 0.05, "y": 0.2 }, "kind": "table", "text": "Categories, Levers, 2011 Value potential ($B), 2016 Adoption rate (%), Average value realized by adopters (%), Value potential realized ($B)", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.341+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c2ecbc60-51c6-4a83-b860-65302e99b08f", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.7, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "US healthcare has seen increased adoption but only captured ~10% of 2011 value estimate", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:54.341+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4210c5c3-dbbf-4599-9392-ab45cdfce4ed", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Value potential realized", "numberRaw": "~10%", "numberKind": "percent", "actionTitle": "US healthcare has seen increased adoption but only captured ~10% of 2011 value estimate", "calloutText": "Slow regulatory processes and monopolistic and segregated industry structure has resulted in only ~10% progress toward realizing BDAA value from 2011", "numberScale": null, "numberValue": 10, "metricFamily": "cost_savings", "numberCurrency": null } ], "tools": [], "frameworks": [], "arcBeats": [ { "to": 9, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 5, "name": "Agitate (Make it worse)", "beatId": "d51be049-4dec-43b6-a2f4-36ba79ee1b19", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Agitate (Make it worse)", "slug": "problem-agitate-solution-agitate-make-it-worse", "status": "active", "canonId": "019dd9b8-0f5a-71dd-bae7-8fadb0d09456", "version": 1, "description": null }, "evidence": "The deck presents various case studies and examples of errors and their consequences, making the problem worse.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 10, "type": "evidence", "title": "The slide uses a hub-and-spoke diagram to illustrate data integration and bar charts to compare model performance across different data inputs.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 77, "componentCount": 8, "textChars": 915, "nDataPoints": 12, "notes": "The slide uses a hub-and-spoke diagram to illustrate data integration and bar charts to compare model performance across different data inputs.", "elementsJson": [ "headline_text", "bullet_list", "infographic", "bar_chart_vertical", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:55.424+00", "seconds": 2.862, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/10", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-10", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Clinical coding data has higher predictive performance than clinical measurements – though both used in combination have higher predictive performance for certain ADEs.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-13e796bb7abd", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.45, "x": 0.52, "y": 0.0065 }, "kind": "chart", "text": "AUC (area under curve)", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1703e159-15e7-43fd-95ca-35c014380bb4", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.45, "x": 0.03, "y": 0.0065 }, "kind": "chart", "text": "Accuracy score", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "41797252-2691-4924-be24-e7a70ab4fa75", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.45, "x": 0.52, "y": 0.0015 }, "kind": "diagram", "text": "Extracting data for machine learning from EHRs", "attrs": null, "canon": { "kind": { "name": "Diagram", "slug": "diagram", "status": "active", "canonId": "019de52c-f9f0-734a-81de-15382ff28c65", "version": 1, "description": "Schematic or relational diagram." }, "tool": null, "subkind": { "name": "Hub and spoke", "slug": "hub-spoke", "status": "active", "canonId": "019de52d-04db-73e6-81ca-a234f2f23fc1", "version": 1, "description": null }, "framework": null }, "subkind": "hub-spoke", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "04cdfd1a-72d9-43b2-a307-a4fa6a3eda06", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.45, "x": 0.03, "y": 0.0015 }, "kind": "list", "text": "Machine learning (random forest model) can be used to accurately predict ADEs (adverse drug events) using data from EHRs (electronic health records). Clinical coding data has higher predictive performance than clinical measurements. Feature selection improves performance. ADEs are ~5% of hospital admissions. Voluntary reporting misses ~94% of ADEs.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "00c688bb-0e27-41e1-a645-68c827903e6c", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AUC: 0.76", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-16b151b72343", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.7, "x": 0.03, "y": 0.95 }, "kind": "source-note", "text": "SOURCE: Zhoa et al, Predictive modeling of structured electronic health records for adverse drug event detection, 2015, BMC Medical Informatics and Decision Making, 15 (Supplement 4):S1", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d22c4b98-ded2-4989-9e2f-dd58e647fae9", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.03, "y": 0.03 }, "kind": "title", "text": "Proof of concept established for machine learning based predictive modelling to detect adverse drug events using EHR data", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "669f1777-80de-4f86-88a0-fb4d61f647a6", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AUC", "numberRaw": "0.76", "numberKind": "plain", "actionTitle": "Proof of concept established for machine learning based predictive modelling to detect adverse drug events using EHR data", "calloutText": "Clinical coding data has higher predictive performance than clinical measurements – though both used in combination have higher predictive performance for certain ADEs.", "numberScale": null, "numberValue": 0.76, "metricFamily": "other", "numberCurrency": null } ], "tools": [], "frameworks": [ { "matchId": "ab2100dd-ee98-4828-afe1-f2a6a98c3519", "evidence": "Diagram showing data sources feeding into a central patient record", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:55.424+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "frameworkName": "hub-spoke" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 11, "type": "evidence", "title": "The slide uses a bar chart to compare the AUC of a random forest machine learning model against five established clinical heuristic scoring systems (CART, Logis", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 74, "componentCount": 7, "textChars": 1378, "nDataPoints": 7, "notes": "The slide uses a bar chart to compare the AUC of a random forest machine learning model against five established clinical heuristic scoring systems (CART, Logistic regression, CURB-65, MEDS, mREMS).", "elementsJson": [ "headline_text", "bullet_list", "photo", "bar_chart_vertical", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:55.415+00", "seconds": 2.816, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/11", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-11", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The machine learning approach has significantly greater predictive performance than other clinical decision rules based models.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:25+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-2f389ba03a8d", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.96, "x": 0.02, "y": 0.0065 }, "kind": "chart", "text": "Accuracy – AUC (area under the receiver operating characteristic curve)", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.415+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "08048f37-3b25-4242-8921-75f0ad15f500", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.46, "x": 0.52, "y": 0.00115 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.415+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e7386375-4fa5-40fd-a83a-d514d9adf4d8", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.48, "x": 0.02, "y": 0.00115 }, "kind": "list", "text": "ER patients with sepsis have a 5% mortality risk; Machine learning (random forest model) can be used to accurately identify patients with sepsis in the ER using data from the Electronic Health Record; The machine learning approach has significantly greater predictive performance than other clinical decision rules based models; The method developed can be automated and applied to EHRs to predict other clinical outcomes of interest; Machine learning methods have potential advantages over traditional heuristic methods as they have greater generalizability, can be developed quickly, and may automatically update as new information becomes available", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.415+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8b0e0395-b8cc-4bcb-845c-e98aa9144b6d", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AUC (Area Under the Curve): 0.86", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:25+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-30dc327bb91a", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.96, "x": 0.02, "y": 0.92 }, "kind": "source-note", "text": "1 Standard statistical measure of diagnostic accuracy 2 CART = Classification and regression tree 3 Difference between the random forest model and all other models SOURCE: Taylor et al, Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach, 2016, Academic Emergency Medicine, Volume 23, Issue 3, 269-278", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.415+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "76ca65ee-04db-48c8-97c4-313281783cb0", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.96, "x": 0.02, "y": 0.03 }, "kind": "title", "text": "Proof of concept established for machine learning based predictive modelling to identify patients in ER with sepsis", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.415+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5a430a05-5f6a-4fc7-87c8-e9a7698358b0", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AUC (Area Under the Curve)", "numberRaw": "0.86", "numberKind": "plain", "actionTitle": "Proof of concept established for machine learning based predictive modelling to identify patients in ER with sepsis", "calloutText": "The machine learning approach has significantly greater predictive performance than other clinical decision rules based models.", "numberScale": null, "numberValue": 0.86, "metricFamily": "other", "numberCurrency": null } ], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 12, "type": "evidence", "title": "The slide highlights both the clinical utility and the data privacy/regulatory challenges of the partnership.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "balanced", "densityScore": 37, "componentCount": 5, "textChars": 378, "nDataPoints": 6, "notes": "The slide highlights both the clinical utility and the data privacy/regulatory challenges of the partnership.", "elementsJson": [ "headline_text", "bullet_list", "photo", "paragraph" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:56.019+00", "seconds": 3.359, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/12", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-12", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.08, "w": 0.94, "x": 0.03, "y": 0.91 }, "kind": "disclaimer", "text": "Footnotes and source citations.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.019+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "81ea5bfc-0d95-45b0-afbc-659d27f509d3", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.45, "x": 0.52, "y": 0.135 }, "kind": "image", "text": "Photo of a smartphone displaying the Streams app interface.", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.019+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6e7a74f7-c4a0-4053-872e-e873d9af8326", "parentComponentId": null }, { "bbox": { "h": 0.75, "w": 0.45, "x": 0.03, "y": 0.135 }, "kind": "list", "text": "Summary of the Streams app, its clinical purpose, the problem of AKI, and the regulatory context.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.019+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "96280b89-bcee-4570-a19b-93be1c96fe6f", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.45, "x": 0.52, "y": 0.6 }, "kind": "list", "text": "Impact metrics including time saved and patients identified.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.019+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b69377a4-1d93-45aa-a2eb-5c6102a1298c", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.94, "x": 0.03, "y": 0.03 }, "kind": "title", "text": "DeepMind and the Royal Free hospital in London have developed an AI-based instant alerting tool to identify patients at risk of AKI", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.019+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "903a59e4-daa0-4351-a03d-26d47469983e", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 13, "type": "evidence", "title": "The slide highlights a specific research study from Tianjin University.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 81, "componentCount": 8, "textChars": 1551, "nDataPoints": 3, "notes": "The slide highlights a specific research study from Tianjin University.", "elementsJson": [ "headline_text", "bullet_list", "photo", "bar_chart_vertical", "big_number", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:22:00.208+00", "seconds": 7.327, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/13", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-13", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Outperforms most other state-of-the-art CADx MRI diagnostic systems", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-edef8f8613d1", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.2, "x": 0.52, "y": 0.65 }, "kind": "chart", "text": "Accuracy – AUC (area under curve) 0.962", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:00.208+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "de6b2ae5-2351-4367-b45d-cba1a92d3673", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.95, "x": 0.02, "y": 0.92 }, "kind": "disclaimer", "text": "1 Standard statistical measure of diagnostic accuracy. SOURCE: Wei Lu et al, A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning, 2017, Computers in Biology and Medicine, Volume 83, Pages 157–165", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:00.208+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "571b6f85-21f5-4923-bff6-4fec97b81975", "parentComponentId": null }, { "bbox": { "h": 0.42, "w": 0.45, "x": 0.52, "y": 0.14 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:00.208+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "899395b1-f4ee-4a9c-b973-5a15d246e0dc", "parentComponentId": null }, { "bbox": { "h": 0.75, "w": 0.48, "x": 0.02, "y": 0.145 }, "kind": "list", "text": "Medical imaging plays an important role in the early detection and diagnosis of breast cancer. Researchers at Tianjin University in China have proposed an automated computer-aided diagnosis (CADx) framework for MRI in breast cancer. The approach combines several machine learning-based techniques, including: Ensemble under-sampling (EUS) for imbalanced data processing, Relief algorithm for feature selection, Subspace method for providing data diversity, Adaboost for improving the base classifier performance. Feature subsets' physical meaning subspaces were built by combining morphological features with each kind of texture or Gabor feature. Proposals were tested using a manually segmented Region of Interest (ROI) data set, containing 438 images of malignant tumours and 1898 images of normal tissues or benign tumours. The approach outperforms most other state-of-the-art CADx MRI diagnostic systems, significantly reducing the rate of false positive classification.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:00.208+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d069d731-89d0-47b9-a1cf-c1ecfcbe80c1", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.25, "x": 0.73, "y": 0.68 }, "kind": "list", "text": "Outperforms most other state-of-the-art CADx MRI diagnostic systems. Significantly reduces rate of false positives.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:00.208+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fdf4dbad-08bf-4259-8de2-dd9a97a90983", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AUC (area under curve): 0.962", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-f2f95c8d5d13", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.85, "x": 0.02, "y": 0.03 }, "kind": "title", "text": "Novel approach proposed for computer-aided MRI-based detection of breast cancer", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:00.208+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "87672854-15ff-481f-9ac7-bfc8d6dfac5f", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AUC (area under curve)", "numberRaw": "0.962", "numberKind": "plain", "actionTitle": "Novel approach proposed for computer-aided MRI-based detection of breast cancer", "calloutText": "Outperforms most other state-of-the-art CADx MRI diagnostic systems", "numberScale": null, "numberValue": 0.962, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "17a177bd-0a4a-4731-a4fc-de705efa601d", "evidence": "Medical imaging plays an important role in the early detection and diagnosis of breast cancer.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.195507+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "1c3c04ca-aa3a-4eb3-a65c-463d0591f387", "evidence": "Outperforms most other state-of-the-art CADx MRI diagnostic systems. Significantly reduces rate of false positives.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.23729+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 14, "type": "analysis", "title": "The slide uses a bar chart to compare AUC scores across three different modeling techniques.", "function": "diagnose", "rawType": "diagnosis", "block": null, "metadata": { "slideType": "diagnosis", "slideTypeCanon": { "name": "Diagnosis", "slug": "diagnosis", "status": "active", "canonId": "019de52d-0cd7-7212-898f-0464041ff8d8", "version": 1, "description": null }, "function": "diagnose", "functionCanon": { "name": "Diagnose", "slug": "diagnose", "status": "active", "canonId": "019de52d-1657-7223-acc5-7437d878c850", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 78, "componentCount": 8, "textChars": 1086, "nDataPoints": 5, "notes": "The slide uses a bar chart to compare AUC scores across three different modeling techniques.", "elementsJson": [ "headline_text", "bullet_list", "photo", "bar_chart_vertical", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:55.902+00", "seconds": 2.981, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/14", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-14", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The model can help target costly therapies to patients with the most urgent need, guide the intensity of clinical monitoring required, and provide prognostic information to patients.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-8e9af7b63416", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.55, "x": 0.03, "y": 0.65 }, "kind": "chart", "text": "AUC scores for Linear regression (0.78), Random forest (0.79), and Boosting (0.79).", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.902+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "348b00d3-bc06-430f-8414-ccf8434cf08e", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.45, "x": 0.52, "y": 0.15 }, "kind": "image", "text": "Anatomical illustration of liver and Hepatitis C virus structure.", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.902+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0375ad11-dcd9-4f78-ad81-2502558cf402", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.35, "x": 0.62, "y": 0.65 }, "kind": "list", "text": "94% negative predictive value. p <0.0001 probability that longitudinal predictive model is superior to baseline.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.902+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6531652d-20e7-435b-a0c4-6664c8aa9f72", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.45, "x": 0.03, "y": 0.18 }, "kind": "list", "text": "Prediction models that incorporate longitudinal clinical data can capture non-linear disease progression in chronic hepatitis C. The approach uses two outcomes measures and a range of predictive variables. The model was constructed using logistic regression, random forest, and boosting. The model can help target costly therapies.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.902+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f71ed01a-cbf0-4470-bb96-bc2782bd69af", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AUC: 0.79", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-93d81f6ce67c", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.95, "x": 0.03, "y": 0.95 }, "kind": "source-note", "text": "1 Standard statistical measure of diagnostic accuracy. SOURCE: Konerman M et al, Improvement of predictive models of risk of disease progression in chronic hepatitis C by incorporating longitudinal data, 2015, Hepatology, 61, 1832-1841", "attrs": { "numbered": true }, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.902+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e38ae371-403c-4d5b-b928-06c3eb4e7220", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.8, "x": 0.03, "y": 0.03 }, "kind": "title", "text": "Machine learning models predict patients at risk of Hep C progression", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.902+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6a0fa691-cc4f-4af7-a1c7-7c3a316b6955", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AUC", "numberRaw": "0.79", "numberKind": "plain", "actionTitle": "Machine learning models predict patients at risk of Hep C progression", "calloutText": "The model can help target costly therapies to patients with the most urgent need, guide the intensity of clinical monitoring required, and provide prognostic information to patients.", "numberScale": null, "numberValue": 0.79, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "6d015149-53ef-40f4-bd90-aceb0e234502", "evidence": "Prediction models that incorporate longitudinal clinical data can capture non-linear disease progression in chronic hepatitis C.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.322427+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "5b0eabaa-4655-4795-af72-1438890f01f0", "evidence": "AUC scores for Linear regression (0.78), Random forest (0.79), and Boosting (0.79).", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.365357+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 14, "from": 4, "loop": { "name": "11_golden_circle", "slug": "11-golden-circle", "status": "active", "bestFor": "Visionary leadership, brand positioning, mission statements", "canonId": "019dd956-6a50-7202-882d-505fcb9922ed", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Why (Belief) -> The How (Process) -> The What (Result)", "description": "Invert the typical pitch by starting with why you exist, rather than what you do", "familyLabel": null }, "matchId": "1b36e03c-871f-4ba9-977e-2461066df8bf", "evidence": "The deck presents various case studies and examples of AI applications in healthcare, using the golden circle framework.", "position": 1, "objective": "Explain why AI is different and how it can be applied in healthcare", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.291422+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 15, "type": "resolution", "title": "The chart is a hybrid bar-line chart showing cumulative admission rates against patient segments.", "function": "quantify_impact", "rawType": "impact_sizing", "block": null, "metadata": { "slideType": "impact_sizing", "slideTypeCanon": { "name": "Impact sizing", "slug": "impact_sizing", "status": "active", "canonId": "019de52d-0d26-773b-aeda-2d1930f5636d", "version": 1, "description": null }, "function": "quantify_impact", "functionCanon": { "name": "Quantify impact", "slug": "quantify_impact", "status": "active", "canonId": "019de52d-1630-720d-b57d-fa7f76bebd8d", "version": 1, "description": null }, "density": "balanced", "densityScore": 42, "componentCount": 5, "textChars": 465, "nDataPoints": 12, "notes": "The chart is a hybrid bar-line chart showing cumulative admission rates against patient segments.", "elementsJson": [ "headline_text", "bullet_list", "bar_chart_vertical", "line_chart", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:55.414+00", "seconds": 2.444, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/15", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-15", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.2, "w": 0.2, "x": 0.75, "y": 0.45 }, "kind": "callout", "text": "Top 1% patients identified are expected to have 67% admission rate and account for 17% of total admissions", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.414+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9373e77b-17f3-460f-9f78-f1ce2bbbfaa8", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.7, "x": 0.05, "y": 0.45 }, "kind": "chart", "text": "Cumulative % of total admissions captured", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.414+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "dc939e87-9461-4609-a1b6-2681a840e2cc", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.9, "x": 0.05, "y": 0.25 }, "kind": "list", "text": "Machine learning to aggregate historical data and understand risk of individual patients of being re-admitted\nSegment patients to understand re-admission rates and develop predictive capabilities", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.414+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1a43fc3f-ff73-4b41-a591-2ec3e185136c", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Cumulative admission rate: 67%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-56720f9637ec", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.9, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Machine learning tool can predict a patient's hospital re-admission risk in the next 6 months", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:55.414+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4e2d601a-e063-4238-8354-f0e384d059dd", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Cumulative admission rate", "numberRaw": "67%", "numberKind": "percent", "actionTitle": "Machine learning tool can predict a patient’s hospital re-admission risk in the next 6 months", "calloutText": "Top 1% patients identified are expected to have 67% admission rate and account for 17% of total admissions", "numberScale": null, "numberValue": 67, "metricFamily": "rate_catchall", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "566b1c17-6880-416a-ae8c-58ed9b39e96a", "evidence": "Cumulative % of total admissions captured", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.44948+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "d06004eb-de21-4806-aa8f-a9069b77581f", "evidence": "The chart demonstrates a concentration of impact (admissions) within a small segment of the population (top 1%).", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:55.414+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "frameworkName": "pareto-principle-80-20" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 16, "type": "evidence", "title": "The slide uses a technical diagram to explain the 'how' behind the operational improvements.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "balanced", "densityScore": 48, "componentCount": 6, "textChars": 491, "nDataPoints": 2, "notes": "The slide uses a technical diagram to explain the 'how' behind the operational improvements.", "elementsJson": [ "headline_text", "bullet_list", "callout_box", "process_diagram" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:56.171+00", "seconds": 3.174, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/16", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-16", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Up to 50% fewer FTEs in A&E; 40-50% shorter patient waiting time", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-d12ce52ff354", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.55, "x": 0.08, "y": 0.34 }, "kind": "image", "text": "TeleTracking Real-Time Locating System diagram", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Infographic", "slug": "infographic", "status": "active", "canonId": "019de52c-fe26-750c-9d7d-9f34e21324e8", "version": 1, "description": null }, "framework": null }, "subkind": "infographic", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.171+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d608b05b-c914-4f6d-ba61-3ec9477eb0dd", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.55, "x": 0.08, "y": 0.225 }, "kind": "list", "text": "Real-time tracking improves data availability and accuracy, allowing for better capacity utilization and automation of routine administration activities", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.171+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "93a07036-aca0-4914-acaa-af83e118bab8", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.25, "x": 0.68, "y": 0.225 }, "kind": "list", "text": "Up to 50% fewer FTEs in A&E\n40-50% shorter patient waiting time", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.171+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b4f16533-62e1-462e-ae29-6191a10ee698", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "A&E headcount reduction: 50%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-d63897b4db7e", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.9, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Tracking hospital operations in real-time allows automation, reducing A&E headcount by up to 50% and cutting patient waiting times in half", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.171+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "01da1434-3f85-4007-8c67-cbae6a8f58e3", "parentComponentId": null } ], "metrics": [ { "metricRaw": "A&E headcount reduction", "numberRaw": "50%", "numberKind": "percent", "actionTitle": "Tracking hospital operations in real-time allows automation, reducing A&E headcount by up to 50% and cutting patient waiting times in half", "calloutText": "Up to 50% fewer FTEs in A&E; 40-50% shorter patient waiting time", "numberScale": null, "numberValue": 50, "metricFamily": "employment", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Before-After-Bridge", "slug": "before-after-bridge", "status": "active", "bestFor": null, "canonId": "019dd956-8604-7188-883f-42370288ad05", "version": 1, "bodyDocId": null, "description": "Narrative structure: Paint the before, show the after, explain the bridge", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "07e7ebf0-0d79-4f40-b376-14badd51e603", "evidence": "Up to 50% fewer FTEs in A&E; 40-50% shorter patient waiting time", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.534184+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 17, "type": "evidence", "title": "The slide uses a 'before-after' framing implicitly by contrasting the initial problem (Summary) with the achieved results (Impact).", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 53, "componentCount": 6, "textChars": 609, "nDataPoints": 4, "notes": "The slide uses a 'before-after' framing implicitly by contrasting the initial problem (Summary) with the achieved results (Impact).", "elementsJson": [ "headline_text", "bullet_list", "screenshot" ], "confidence": 0.95, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:56.666+00", "seconds": 3.085, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/17", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-17", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "€15-20M saved in absenteeism costs", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-3665459dca0e", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.6, "x": 0.05, "y": 0.045 }, "kind": "image", "text": "Analytic and Executive Dashboards showing absenteeism metrics", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Screenshot", "slug": "screenshot", "status": "active", "canonId": "019de52c-fd87-7509-8391-3d79fb339379", "version": 1, "description": null }, "framework": null }, "subkind": "screenshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.666+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6e2d79bf-ce33-4522-a88a-55c625862d24", "parentComponentId": null }, { "bbox": { "h": 0.3, "w": 0.25, "x": 0.7, "y": 0.048 }, "kind": "list", "text": "€15-20M saved in absenteeism costs; Root cause drivers of attrition by cohort/cluster; Tailored interventions based on individual risk lists", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.666+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "67fa9563-3409-4ffb-bfc5-3d633f518c86", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.9, "x": 0.05, "y": 0.25 }, "kind": "list", "text": "Leading European financial institution was facing above-industry employee absenteeism; Significant loss of value estimated at 20m USD yearly for 2k employees; Strict regulatory environment prohibiting sanctions around absenteeism", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.666+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ca1b4731-09fe-4e08-b6e0-136b8423afee", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Absenteeism costs: €15-20M", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-397f38560a86", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.9, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Data-driven employee management can allow companies to identify the root causes of absenteeism and reduce related costs", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.666+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "549fbf83-640b-40cd-949a-6553e3fe9daa", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Absenteeism costs", "numberRaw": "€15-20M", "numberKind": "money", "actionTitle": "Data-driven employee management can allow companies to identify the root causes of absenteeism and reduce related costs", "calloutText": "€15-20M saved in absenteeism costs", "numberScale": null, "numberValue": 15, "metricFamily": "cost_savings", "numberCurrency": "€" } ], "tools": [ { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "54e94461-f998-4eba-81f2-2b04137ec928", "evidence": "€15-20M saved in absenteeism costs; Root cause drivers of attrition by cohort/cluster; Tailored interventions based on individual risk lists", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:15:51.621362+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "c16444f5-f918-49c0-a7ac-aa75dbd49751", "evidence": "Contrasts the initial problem state with the post-intervention impact results.", "framework": null, "confidence": 0.85, "extraction": { "at": "2026-05-02 19:21:56.666+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "frameworkName": "before-after-framing" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 18, "type": "resolution", "title": "The slide uses a waterfall-style chart to aggregate value across different levers, with a corresponding impact summary on the right.", "function": "quantify_impact", "rawType": "impact_sizing", "block": null, "metadata": { "slideType": "impact_sizing", "slideTypeCanon": { "name": "Impact sizing", "slug": "impact_sizing", "status": "active", "canonId": "019de52d-0d26-773b-aeda-2d1930f5636d", "version": 1, "description": null }, "function": "quantify_impact", "functionCanon": { "name": "Quantify impact", "slug": "quantify_impact", "status": "active", "canonId": "019de52d-1630-720d-b57d-fa7f76bebd8d", "version": 1, "description": null }, "density": "dense", "densityScore": 57, "componentCount": 7, "textChars": 404, "nDataPoints": 24, "notes": "The slide uses a waterfall-style chart to aggregate value across different levers, with a corresponding impact summary on the right.", "elementsJson": [ "headline_text", "bar_chart_stacked", "infographic", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:56.998+00", "seconds": 2.648, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/18", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-18", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.7, "w": 0.4, "x": 0.55, "y": 0.18 }, "kind": "chart", "text": "Impact metrics (life expectancy, consumer value, cost savings)", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Horizontal bar chart", "slug": "bar-horizontal", "status": "active", "canonId": "019de52c-fec4-7221-986b-1cb5f5e84b1f", "version": 1, "description": null }, "framework": null }, "subkind": "bar-horizontal", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0e19f807-b296-4efd-8e1c-685968201dcd", "parentComponentId": null }, { "bbox": { "h": 0.75, "w": 0.4, "x": 0.12, "y": 0.15 }, "kind": "chart", "text": "Global Value created, $B", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Waterfall chart", "slug": "waterfall", "status": "active", "canonId": "019de52d-002e-733e-b5cf-dd3beb6692cc", "version": 1, "description": null }, "framework": null }, "subkind": "waterfall", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3eb1b1b4-7565-420e-b145-bd27848b0acc", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.95, "x": 0.02, "y": 0.95 }, "kind": "disclaimer", "text": "1 Not sized given focus on analytics in healthcare delivery only 2 National Health Expenditures SOURCE: McKinsey Global Institute analysis", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3944180e-3395-4f5f-ac16-42e31a5c62fe", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.25, "x": 0.7, "y": 0.03 }, "kind": "legend", "text": "Life extension, Cost savings, Quality of life, Additional", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1b2d71bf-0e86-4fb3-9557-a50fdba51bf9", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.35, "x": 0.02, "y": 0.18 }, "kind": "list", "text": "Levers A-E and associated numbered initiatives 1-8", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9b58fe32-9068-4904-8e63-9240705fbba5", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Global Value created: $12,700B", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2b9-b6e14d001a2f", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.4, "x": 0.02, "y": 0.03 }, "kind": "title", "text": "Outlook: Significant further value at stake", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b86c220b-fa4f-4e49-b466-6b8afe4f5a4f", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Global Value created", "numberRaw": "$12,700B", "numberKind": "money", "actionTitle": "Outlook: Significant further value at stake", "calloutText": null, "numberScale": "b", "numberValue": 12.7, "metricFamily": "other", "numberCurrency": "$" } ], "tools": [ { "tool": { "name": "Waterfall chart", "slug": "waterfall-chart", "status": "active", "bestFor": null, "canonId": "e2799da3-725f-44a9-a093-570f1f388e64", "version": 1, "bodyDocId": null, "description": null, "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "8ea9cca8-3645-46a4-80cc-b3ec0e2a465f", "evidence": "Global Value created, $B", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:15:51.705042+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "bc607312-039b-409b-abdc-9a5cc3ce889c", "evidence": "Quantifies potential value creation across multiple levers.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:56.998+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "frameworkName": "impact_sizing" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 18, "from": 18, "loop": { "name": "27_cost_of_inaction", "slug": "27-cost-of-inaction", "status": "active", "bestFor": "Urgent budget requests, compliance, risk mitigation", "canonId": "019dd956-70d1-7395-a15b-857ba858b394", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point", "description": "Quantify what happens if the audience does nothing", "familyLabel": null }, "matchId": "7e5a1b2d-6045-4ae5-9071-3c7f16a0a952", "evidence": "The deck presents a slide on the significant further value at stake, highlighting the cost of inaction.", "position": 0, "objective": "Highlight the cost of inaction in healthcare error prevention", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:07:17.25806+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 19, "type": "setup", "title": "The slide uses a dot-matrix visualization to represent barrier intensity (Major, Minor, Not a barrier) across two industry sectors.", "function": "compare_peers", "rawType": "comparison_table", "block": null, "metadata": { "slideType": "comparison_table", "slideTypeCanon": { "name": "Comparison table", "slug": "comparison_table", "status": "active", "canonId": "019de52d-0a06-73f8-8813-fe022fab1de2", "version": 1, "description": null }, "function": "compare_peers", "functionCanon": { "name": "Compare peers", "slug": "compare_peers", "status": "active", "canonId": "019de52d-1453-72ba-a367-9ba3d34c1630", "version": 1, "description": null }, "density": "balanced", "densityScore": 29, "componentCount": 4, "textChars": 278, "nDataPoints": 36, "notes": "The slide uses a dot-matrix visualization to represent barrier intensity (Major, Minor, Not a barrier) across two industry sectors.", "elementsJson": [ "headline_text", "comparison_table", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:57.041+00", "seconds": 2.622, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/19", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-19", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.1, "w": 0.3, "x": 0.65, "y": 0.02 }, "kind": "legend", "text": "Internal Organizational barriers, External barriers to data, Major barrier, Minor barrier, Not a barrier", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.041+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8be168c1-389b-4a55-ab84-b420f2f5cd9d", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.95 }, "kind": "source-note", "text": "SOURCE: McKinsey Global Institute analysis", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.041+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3100869c-df8d-4cf7-b8fd-5771fc769fd9", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.9, "x": 0.05, "y": 0.2 }, "kind": "table", "text": "Comparison of barriers across 12 categories for Location based data and Healthcare", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.041+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "02209b10-6eec-4925-99c0-cabadd401152", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.5, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Barriers in healthcare vs. location based services", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.041+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ed764eca-3e96-4d08-9d43-16053abb7c0f", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Comparison frame", "slug": "comparison-frame", "status": "active", "bestFor": null, "canonId": "019dd9e1-484b-7399-a4fc-d14644b99f93", "version": 1, "bodyDocId": null, "description": "Two or more states/subjects placed side by side to expose a gap.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "f055cc6e-9295-4eeb-96d7-7626ab9dc98e", "evidence": "Comparison of barriers across 12 categories for Location based data and Healthcare", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.789474+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [ { "matchId": "4563ade7-45c3-4c23-b4d6-f1ffe5699609", "evidence": "The slide compares two sectors across a shared set of criteria.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:21:57.041+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "frameworkName": "comparison_table" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 20, "type": "setup", "function": "summarize", "rawType": "agenda", "block": null, "metadata": { "slideType": "agenda", "slideTypeCanon": { "name": "Agenda", "slug": "agenda", "status": "active", "canonId": "019de52d-061b-7470-b138-3ffa5e612cce", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "sparse", "densityScore": 12, "componentCount": 3, "textChars": 201, "nDataPoints": 0, "notes": null, "elementsJson": [ "numbered_list", "other" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:56.67+00", "seconds": 2.227, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/20", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-20", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.7, "w": 0.38, "x": 0.6, "y": 0.15 }, "kind": "image", "text": "Large 3D question mark", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "41e903b0-0a7f-41a2-9b29-5a8b82ff598a", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.54, "x": 0.01, "y": 0.24 }, "kind": "list", "text": "1. Why is Artificial Intelligence/Machine Learning different, and why now?\n2. Where is the opportunity in patient safety/patient care?\n3. How can we enable change?", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4570e3ce-4847-4521-84e3-85886c42d303", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.23, "x": 0.01, "y": 0.03 }, "kind": "title", "text": "Agenda for today", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:56.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "569a382e-2cf8-415f-89cb-dcebe74a75ee", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 21, "type": "setup", "title": "The slide uses a numbered list format to structure common client inquiries regarding AA transformation.", "function": "frame_problem", "rawType": "key_messages", "block": null, "metadata": { "slideType": "key_messages", "slideTypeCanon": { "name": "Key messages", "slug": "key_messages", "status": "active", "canonId": "019de52d-0712-703f-89f5-bda6688faf3f", "version": 1, "description": null }, "function": "frame_problem", "functionCanon": { "name": "Frame problem", "slug": "frame_problem", "status": "active", "canonId": "019de52d-13db-753e-ad70-e9b2d0dab398", "version": 1, "description": null }, "density": "balanced", "densityScore": 28, "componentCount": 3, "textChars": 571, "nDataPoints": 0, "notes": "The slide uses a numbered list format to structure common client inquiries regarding AA transformation.", "elementsJson": [ "headline_text", "numbered_list", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:57.123+00", "seconds": 2.532, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/21", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-21", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.03, "w": 0.1, "x": 0.85, "y": 0.08 }, "kind": "legend", "text": "Key focus areas", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.123+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "83f26260-cd47-4575-a348-19be619ae054", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.9, "x": 0.05, "y": 0.185 }, "kind": "list", "text": "1. What is my vision and strategy? 2. How do I identify and prioritise use cases? 3. What kind of data infrastructure do I require? 4. Which skills and capabilities do I need? 5. What are the processes required for data management? 6. What are data quality principles and policies? 7. What organizational model do I need? 8. What are other innovative data technologies? 9. How do I manage the transition effectively? 10. How do I ensure an agile way of working?", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.123+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b956ed1c-44e2-41f3-961e-24a9df5fe234", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.7, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Advanced analytics capabilities and change management are key to a successful AA transformation", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.123+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9cbe2972-05dd-4a75-99cd-35c81e39e5a7", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 22, "type": "setup", "title": "The slide uses a before-and-after comparison to illustrate the benefits of a data lake architecture.", "function": "present_solution", "rawType": "diagnosis", "block": null, "metadata": { "slideType": "diagnosis", "slideTypeCanon": { "name": "Diagnosis", "slug": "diagnosis", "status": "active", "canonId": "019de52d-0cd7-7212-898f-0464041ff8d8", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "balanced", "densityScore": 46, "componentCount": 6, "textChars": 539, "nDataPoints": 0, "notes": "The slide uses a before-and-after comparison to illustrate the benefits of a data lake architecture.", "elementsJson": [ "process_diagram", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:57.185+00", "seconds": 2.561, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/22", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-22", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "From “spaghetti” architecture with redundant DWHs and staging areas and replicated data To all data into one repository and consolidation of all redundant DWHs and staging areas", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:28+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2bb-9a4473d86ec6", "parentComponentId": null }, { "bbox": { "h": 0.75, "w": 0.92, "x": 0.04, "y": 0.15 }, "kind": "diagram", "text": "Before-and-after architecture diagram", "attrs": null, "canon": { "kind": { "name": "Diagram", "slug": "diagram", "status": "active", "canonId": "019de52c-f9f0-734a-81de-15382ff28c65", "version": 1, "description": "Schematic or relational diagram." }, "tool": null, "subkind": { "name": "Process flow", "slug": "process", "status": "active", "canonId": "019de52d-039c-718f-ad3a-efe9c4b3c838", "version": 1, "description": null }, "framework": null }, "subkind": "process", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cda7dd1b-e175-4ecb-9b54-1ad93281ec56", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.42, "x": 0.108, "y": 0.15 }, "kind": "paragraph", "text": "From “spaghetti” architecture with redundant DWHs and staging areas and replicated data", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2dcae0a9-e2d2-42b1-bc91-04764474f303", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.42, "x": 0.55, "y": 0.15 }, "kind": "paragraph", "text": "To all data into one repository and consolidation of all redundant DWHs and staging areas", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a5068e20-6883-4f17-b80c-cec880fb9961", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.04, "y": 0.95 }, "kind": "source-note", "text": "1 Fundamental instrument to use data in a structured way and derive insights", "attrs": { "numbered": true }, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8a6c965a-16a4-4361-acdb-e4cb62374bdf", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.92, "x": 0.04, "y": 0.03 }, "kind": "title", "text": "3 “Data lake” is an indispensable enabler of the analytics transformation", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6494ac21-af0a-4abf-9570-e496c5ea0a17", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Before-After-Bridge", "slug": "before-after-bridge", "status": "active", "bestFor": null, "canonId": "019dd956-8604-7188-883f-42370288ad05", "version": 1, "bodyDocId": null, "description": "Narrative structure: Paint the before, show the after, explain the bridge", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "a186e3a8-b93c-42aa-bff2-f43afd4d2bcd", "evidence": "From “spaghetti” architecture with redundant DWHs and staging areas and replicated data To all data into one repository and consolidation of all redundant DWHs and staging areas", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:15:51.957017+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "c12a2afc-ec5e-4b51-8235-10d9d56f9eeb", "evidence": "The slide explicitly contrasts a 'spaghetti' architecture with a 'Big Data lake' architecture.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:21:57.185+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "frameworkName": "before-after-framing" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 23, "type": "setup", "title": "The slide uses a Venn diagram to show role overlap and a table to define specific skill sets for key roles.", "function": "present_framework", "rawType": "org_design", "block": null, "metadata": { "slideType": "org_design", "slideTypeCanon": { "name": "Org design", "slug": "org_design", "status": "active", "canonId": "019de52d-0dc5-718c-a94d-542c49b7bf6a", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "balanced", "densityScore": 38, "componentCount": 6, "textChars": 353, "nDataPoints": 0, "notes": "The slide uses a Venn diagram to show role overlap and a table to define specific skill sets for key roles.", "elementsJson": [ "headline_text", "venn_diagram", "comparison_table", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:57.846+00", "seconds": 3.21, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/23", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-23", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Understands business problem and translates into technical language and vice versa.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:28+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2ba-fbfab52b2efc", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.45, "x": 0.05, "y": 0.17 }, "kind": "diagram", "text": "Venn diagram showing overlap between Advanced Analytics, IT/Big Data management, and Traditional business managers.", "attrs": null, "canon": { "kind": { "name": "Diagram", "slug": "diagram", "status": "active", "canonId": "019de52c-f9f0-734a-81de-15382ff28c65", "version": 1, "description": "Schematic or relational diagram." }, "tool": null, "subkind": { "name": "Venn diagram", "slug": "venn", "status": "active", "canonId": "019de52d-0463-710d-b529-cce18d828d2f", "version": 1, "description": null }, "framework": null }, "subkind": "venn", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "129a22e5-5ded-40f8-bf92-68b8a0909057", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.25, "x": 0.05, "y": 0.75 }, "kind": "image", "text": "Network of people icon", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "57a1073e-6b7c-467c-b3c8-abd1adf1f027", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.45, "x": 0.5, "y": 0.165 }, "kind": "table", "text": "Roles and typical profiles needed", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6d525e18-d0b0-4c2c-8284-3a40931a7ed7", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.05, "y": 0.03 }, "kind": "title", "text": "Data analytics teams needs different skills to be successful", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "68a6e89d-b510-4e29-a2ad-59569c215cc2", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.3, "x": 0.05, "y": 0.01 }, "kind": "title", "text": "WHICH SKILLS AND CAPABILITIES DO I NEED?", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d85cbff8-a709-400e-a0ac-5344ba2237dc", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [ { "matchId": "284bccfd-1bfe-4c6a-9d2c-af935d498cf7", "evidence": "Overlapping circles used to categorize roles", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:21:57.846+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 23, "frameworkName": "venn-diagram" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 24, "type": "setup", "title": "The slide uses a spectrum-based framework to categorize data governance models.", "function": "compare_options", "rawType": "org_design", "block": null, "metadata": { "slideType": "org_design", "slideTypeCanon": { "name": "Org design", "slug": "org_design", "status": "active", "canonId": "019de52d-0dc5-718c-a94d-542c49b7bf6a", "version": 1, "description": null }, "function": "compare_options", "functionCanon": { "name": "Compare options", "slug": "compare_options", "status": "active", "canonId": "019de52d-167f-7038-aebc-70a9d2e0e33b", "version": 1, "description": null }, "density": "sparse", "densityScore": 19, "componentCount": 4, "textChars": 257, "nDataPoints": 0, "notes": "The slide uses a spectrum-based framework to categorize data governance models.", "elementsJson": [ "headline_text", "action_title", "comparison_table", "process_diagram", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:22:03.522+00", "seconds": 8.635, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/24", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-24", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.7, "w": 0.9, "x": 0.05, "y": 0.2 }, "kind": "framework", "text": "Organizational Archetype Spectrum", "attrs": null, "canon": { "kind": { "name": "Framework", "slug": "framework", "status": "active", "canonId": "019de52c-fa18-77c6-b10a-ccb8277ac0fa", "version": 1, "description": "Named conceptual framework instance." }, "tool": null, "subkind": { "name": "Framework instance", "slug": "instance", "status": "active", "canonId": "019de52d-05a2-72af-be0b-7edc60708a03", "version": 1, "description": null }, "framework": null }, "subkind": "instance", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:03.522+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b5815041-b723-4c97-87ad-3a287f173890", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.3, "x": 0.65, "y": 0.13 }, "kind": "legend", "text": "Organizational unit vs Data organization legend", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:03.522+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8526e34e-e888-4d4b-9856-295df85d1fa1", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.9, "x": 0.05, "y": 0.2 }, "kind": "table", "text": "Comparison matrix of four data governance models across Description and Evaluation criteria.", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:03.522+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c2cc3a14-4b40-4023-9dac-c3bbe5d52e8e", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.03 }, "kind": "title", "text": "Choosing the right organizational archetype is essential for managing data governance", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:22:03.522+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c519d8fb-08e5-40a3-b1a2-4e0a17602925", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [ { "matchId": "b35ac261-c603-44d6-95b4-ce25686c426a", "evidence": "The slide uses a structured grid to compare four distinct organizational archetypes across two dimensions (Description and Evaluation).", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:22:03.522+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "frameworkName": "matrix-nxn" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 25, "type": "setup", "title": "The slide uses a numbered list format to structure the key strategic questions for AA transformation.", "function": "frame_problem", "rawType": "agenda", "block": null, "metadata": { "slideType": "agenda", "slideTypeCanon": { "name": "Agenda", "slug": "agenda", "status": "active", "canonId": "019de52d-061b-7470-b138-3ffa5e612cce", "version": 1, "description": null }, "function": "frame_problem", "functionCanon": { "name": "Frame problem", "slug": "frame_problem", "status": "active", "canonId": "019de52d-13db-753e-ad70-e9b2d0dab398", "version": 1, "description": null }, "density": "sparse", "densityScore": 24, "componentCount": 2, "textChars": 556, "nDataPoints": 0, "notes": "The slide uses a numbered list format to structure the key strategic questions for AA transformation.", "elementsJson": [ "headline_text", "numbered_list", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:57.662+00", "seconds": 2.68, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/25", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-25", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.7, "w": 0.9, "x": 0.05, "y": 0.17 }, "kind": "list", "text": "1. What is my vision and strategy? 2. How do I identify and prioritise use cases? 3. What kind of data infrastructure do I require? 4. Which skills and capabilities do I need? 5. What are the processes required for data management? 6. What are data quality principles and policies? 7. What organizational model do I need? 8. What are other innovative data technologies? 9. How do I manage the transition effectively? 10. How do I ensure an agile way of working?", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.662+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5df5d8c1-dba8-4fb2-a132-d133dbde0d0b", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.9, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Advanced analytics capabilities and change management are key to a successful AA transformation", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.662+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "997dc820-4c05-41b7-ab75-4b21533178ae", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "4d542a03-3a55-462f-86a3-c0497c085de3", "evidence": "The slide contains a numbered list with specific points.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:15:51.72328+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [ { "matchId": "25cbffe2-e766-4274-94bd-dee70061068b", "evidence": "Numbered list of key strategic questions", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:57.662+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "frameworkName": "list-presentation" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 26, "type": "resolution", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "balanced", "densityScore": 37, "componentCount": 3, "textChars": 732, "nDataPoints": 1, "notes": null, "elementsJson": [ "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:21:57.619+00", "seconds": 2.584, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b638-e91d3b8478cc/26", "deck": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc", "deckAnchor": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc#slide-26", "deckJson": "/decks/019dd923-5ca1-7489-b638-e91d3b8478cc.json" }, "components": [ { "bbox": { "h": 0.75, "w": 0.82, "x": 0.09, "y": 1 }, "kind": "list", "text": "1. Huge progress to predict and prevent risk/faults across industries.\n2. AI in healthcare is overhyped by stories about replacing doctors and making decisions, and under used for crucial safety and efficiency interventions\n3. The longer term opportunity could be worth 3-13 % of GDP\n4. Healthcare is a laggard in adoption, as opposed, for example to geolocation sector.\n5. Most common mistakes/barriers include: lack of enabling data integration / interoperability, lack of investment into skills eg translators, and ineffective organizational set up\n6. Ministers of Health and medical profession have an important role to create the regulatory context and conditions for the barriers to be overcome", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.619+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a6855a62-5652-4ea4-b3e2-7d7cb11aae6c", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "GDP: 3-13%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 13:33:28+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-d3bc-73c4-a2bb-a8cd482e5c3c", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.33, "x": 0.09, "y": 0.04 }, "kind": "title", "text": "Key take away messages", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:21:57.619+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cbb75dac-b4df-45f1-b171-c44772d1a262", "parentComponentId": null } ], "metrics": [ { "metricRaw": "GDP", "numberRaw": "3-13%", "numberKind": "percent", "actionTitle": null, "calloutText": null, "numberScale": null, "numberValue": -13, "metricFamily": "market_size", "numberCurrency": null } ], "tools": [ { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "e241661c-c763-4c10-ab30-d1cab1b197f9", "evidence": "The slide contains a numbered list with key take away messages.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:15:51.800306+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [ { "matchId": "f9f68ffe-7910-4667-85aa-da10ddc492ac", "evidence": "The slide uses a numbered list to present key takeaways.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:21:57.619+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "frameworkName": "list-presentation" } ], "arcBeats": [ { "to": 26, "arc": { "name": "Problem-Agitate-Solution", "slug": "problem-agitate-solution", "status": "active", "bestFor": "Sales pitches, urgency-driven, competitive displacement", "canonId": "019dd956-5ec6-70f9-9fd8-fdbaaff39acf", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Problem (Identify pain) -> Agitate (Make it worse) -> Solution (Provide relief)", "description": null, "familyLabel": null }, "from": 10, "name": "Solution (Provide relief)", "beatId": "9b6e4ffe-95ca-40d4-92d5-70f2cd8f60f8", "matchId": "93feb748-1e17-4712-b171-9dee246c4222", "beatType": { "name": "Solution (Provide relief)", "slug": "problem-agitate-solution-solution-provide-relief", "status": "active", "canonId": "019dd9b8-0fee-73e9-9ae5-799c7f3895cd", "version": 1, "description": null }, "evidence": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes.", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true } ], "arcBeats": [ { "from": 1, "to": 4, "label": "Problem (Identify pain)", "description": "The deck starts by highlighting the problem of healthcare errors and their consequences." }, { "from": 5, "to": 9, "label": "Agitate (Make it worse)", "description": "The deck presents various case studies and examples of errors and their consequences, making the problem worse." }, { "from": 10, "to": 26, "label": "Solution (Provide relief)", "description": "The deck offers AI as a solution to prevent healthcare errors and improve patient outcomes." } ], "loops": [ { "from": 18, "to": 18, "label": "Cost Of Inaction", "description": "Highlight the cost of inaction in healthcare error prevention" }, { "from": 4, "to": 14, "label": "Golden Circle", "description": "Explain why AI is different and how it can be applied in healthcare" } ] }