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Artificial intelligence enhances ovarian cancer diagnostics

Providing general pathologists with additional tools to achieve a higher interobserver agreement would support optimal diagnostics and the timeliest and best possible treatment approach.

(University of British Columbia) — Ovarian cancer impacts over 3,100 Canadian women each year, making it the most lethal of all female reproductive cancers. A new study led by Dr. Ali Bashashati, a UBC and Vancouver Coastal Health Research Institute researcher, reveals how artificial intelligence (AI) can aid in the diagnosis of ovarian cancer to improve patient outcomes.

The study, recently published in Modern Pathology, builds on the understanding that ovarian cancer is not a single disease, but several distinct subtypes, called histotypes.

Dr. Bashashati and his team compared ovarian cancer disease classifications made by an AI machine learning-based model against those of a team of expert gynecologic pathologists who specialize in the diagnosis of female reproductive cancers. (…)