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Machine Learning Takes Disease Detection to the Next Level

By June 26, 2018No Comments

Inside the Department of Pathology and Laboratory Medicine at Vancouver General Hospital (VGH), a clinician peers through a microscope. She is looking at a thin slice from a block of paraffin wax embedded with tissue samples, searching for clues to cure disease. VGH neuropathologist and VCHRI researcher Dr. Stephen Yip calls this the analogue version of histology—the study of the structure of tissues at the microscopic level. Research he and colleagues are conducting is paving the way for histology 2.0 in the age of digital technology.

Yip and Adrian Levine, a resident of pathology and laboratory medicine at VGH, are researching how software programs that use deep learning can add a layer of quality control to diagnosing diseases from tissue samples. Deep learning here refers to computer software that uses algorithms to recognize what data represents, such as curves and lines in an image. This is similar to technology found in self-driving cars, which uses machine learning to detect features in the landscape.