Peer review is a viable application for artificial intelligence (AI) software that identifies abnormalities on X-rays, say radiologists from New Delhi who described this application at the 2019 RSNA annual meeting. The researchers conducted a quality assurance study evaluating commercial AI software designed to detect abnormalities in chest radiographs.

Noting that quality control in radiology is usually performed by random double reads, the RADPEER approach, or collating information about clinical correlation session presenter Vasanthakumar K Venugopal, MBBS, MD, said, “Numerous studies have shown that these methods are not optimized to discover cases with diagnostic error. Thus, they have inherent limitations to improve quality. Non-random peer review processes are time consuming and not exhaustive. My colleagues and I wanted to determine if an AI tool could help or improve the peer review process,” added Dr. Venugopal, of the Center for Advanced Research in Imaging, Neuroscience and Genomics of Mahajan Imaging.

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