Opportunistic AI for Medical Scans

Director, Scripps Translational Science Institute; Professor of Molecular Medicine, The Scripps Research Institute, La Jolla, CaliforniaServe as a director, officer, partner, employee, advisor, consultant, or trustee for: Dexcom; Illumina; Molecular Stethoscope; Quest Diagnostics; Blue Cross Blue Shield Association

Better because it identified substantially more people who would benefit from statin therapy, the main output of the ASCVD risk score. There are more than 20 million chest CT scans done in the United States per year. But they aren't being used to detectOver the past 8 years, we've had ample evidence from hundreds of studies in radiology that deep learning AI can potentially be used to promote accuracy of medical image interpretation, across all different types of scans . But that body of data is centered on a focused interpretation of the scan, such as pneumonia or a lung nodule on a chest X-ray.

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Transparent medical image AI via an image–text foundation model grounded in medical literatureBuilding trustworthy and transparent image-based medical artificial intelligence (AI) systems requires the ability to interrogate data and models at all stages of the development pipeline, from training models to post-deployment monitoring.
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CT scans look inside a California condor eggAndrew Paul is Popular Science‘s staff writer covering tech news. Previously, he was a regular contributor to The A.V. Club and Input, and has had recent work featured by Rolling Stone, Fangoria, GQ, Slate, NBC, as well as McSweeney’s Internet Tendency. He lives outside Indianapolis.
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