Harvard, MIT researchers harness deep learning for more accurate breast cancer pathology

Breast cancer biopsy–Courtesy of Harvard U. Researchers at Beth Israel Deaconess Medical Center and Harvard Medical School have worked together to create an analysis of breast cancer pathology that incorporates artificial intelligence. They found that their system–and the evaluation by pathologists themselves–worked better when used in conjunction than either did alone. In an evaluation of slides of lymph node cells, the automated diagnostic method was accurate about 92% of the time. This was almost as accurate as human pathologists–who are about 96% correct. But when combined–the results were even better. “The truly exciting thing was when we combined the pathologist’s analysis with our automated computational diagnostic method, the result improved to 99.5% accuracy,” said pathologist Dr. Andrew Beck, director of bioinformatics at the Cancer Research Institute at Beth Israel Deaconess…


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