Researchers from the University of North Carolina have called for more rigorous testing of artificial intelligence (AI)-powered medical devices, following a comprehensive study of nearly three decades of U.S. Food and Drug Administration (FDA) authorizations.
The study, published in Nature Medicine, found that nearly half of AI medical devices authorized by the FDA were not based on real patient data, raising concerns about their safety and effectiveness in real-world patient care.
Some devices used simulated images, not real patient data, which technically didn’t qualify as testing in real patients, also known as clinical validation.
Although AI medical devices serve many useful purposes, including detection of cancer and strokes on radiology scans, this study shows they also bring with them potential dangers.
“We shared our findings with directors at the FDA who oversee medical device regulation, and we expect our work will inform their regulatory decision making,” Sammy Chouffani El Fassi, a doctor of medicine candidate at the University of North Carolina Medical School and first author, said in an interview with The Epoch Times. […]
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