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  "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
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      "text": "As such, the AI could reliably remove 36.4% of normal chest X-rays from a primary health care population data set with a minimal number of false negatives, leading to effectively no compromise on patient safety and a potential significant reduction of workload.",
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      "text": "Chest X-ray -> ChestLink -> (No findings -> Generated Normal report) / (Suspect -> Radiologist report as usual)",
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      "text": "Due to a shortage of radiologists and an increasing volume of imaging, the diagnostic task of assessing which X-rays contain disease and which don't is challenging.\nOxipit's ChestLink is a computer vision system that is tasked with identifying scans that are normal.\nThe system is trained on over a million diverse images. In a retrospective study of 10,000 chest X-rays of Finnish primary health care patients, the AI achieved a sensitivity of 99.8% and specificity of 36.4 % for recognising clinically significant pathology on a chest X-ray.\nAs such, the AI could reliably remove 36.4% of normal chest X-rays from a primary health care population data set with a minimal number of false negatives, leading to effectively no compromise on patient safety and a potential significant reduction of workload.",
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      "text": "Lithuanian startup Oxipit received the industry's first autonomous certification for their computer vision-based diagnostic. The system autonomously reports on chest X-rays that feature no abnormalities, removing the need for radiologists to look at them.",
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