Researchers showed that AI assistance potentially could improve breast-cancer screening by reducing the number of false positives without missing true positives.
"False positives are when you call a patient back for additional testing, and it turns out to be benign," explained senior author Richard L. Wahl, MD, a professor of radiology at Washington University's Mallinckrodt Institute of Radiology and a professor of radiation oncology."That causes a lot of unnecessary anxiety for patients and consumes medical resources.
For example, consider the largest dataset, which contained 11,592 mammograms. When scaled to 10,000 mammograms , AI identified 34.9% as negative. If those 3,485 negative mammograms had been removed from the workload, radiologists would have made 897 callbacks for diagnostic exams, a reduction of 23.7% from the 1,159 they made in reality. At the next step, 190 people would have been called in a second time for biopsies, a reduction of 6.9% from the 200 in reality.
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