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AI can stratify risk of COVID-19 based on chest x-rays


After assessing a modified version of a commercially available deep-learning algorithm developed initially to detect tuberculosis, researchers led by Diego Hipolito Canario of the University of North Carolina at Chapel Hill found in a clinical study that the software yielded a high level of accuracy in detecting radiographic abnormalities indicative of COVID-19 on chest x-rays.


What’s more, the algorithm’s risk scores had high positive predictive value and negative predictive value in comparison with real-time reverse transcription polymerase chain reaction (RT-PCR) testing in those…



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