AI Achieves Near-Human Detection of Breast Cancer

Pathologists still do the bulk of their diagnosis of metastatic cancer cells in tissue and lymph nodes by hand, putting slides under a microscope and looking for signature irregularities they're trained to see. Recent advances in computer technology, however, particularly in artificial intelligence (AI), have begun to teach machines to do this kind of detection with growing rates of improvement. Now, a research team from Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School have developed a form of AI that can interpret these pathology images with accuracy levels of 92.5 percent. Moreover, when the two are used in combination, the detection rate approaches 100 percent (approximately 99.5 percent). Their AI method is a form of deep learning, in which the system attempts to replicate the activity of the human neocortex through artificial neural networks.