In DepthClinical Research

Medicine contends with how to use artificial intelligence

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Science  21 Jun 2019:
Vol. 364, Issue 6446, pp. 1119-1120
DOI: 10.1126/science.364.6446.1119

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Artificial intelligence (AI) is poised to upend the practice of medicine, boosting the efficiency and accuracy of diagnosis in specialties that rely on images, like radiology and pathology. But as the technology gallops ahead, experts are grappling with its potential downsides. One major concern: Most AI software is designed and tested in one hospital, and it risks faltering when transferred to another. Last month, in the Journal of the American College of Radiology, U.S. government scientists, regulators, and doctors published a road map describing how to convert research-based AI into software for medical imaging on patients. Among other things, the authors urged more collaboration across disciplines in building and testing AI algorithms and intensive validation of them before they reach patients. Right now, most AI in medicine is used in research, but regulators have already approved some algorithms for radiologists. Many studies are testing algorithms to read x-rays, detect brain bleeds, pinpoint tumors, and more.