Deep learning reveals valuable clues about kidney cancer in pathology slides

A team of Dana-Farber researchers has identified a potential new way to assess clinically valuable features of clear cell renal cell carcinoma (ccRCC), a form of kidney cancer, using image processing with deep learning. Their AI-based assessment tool evaluates two-dimensional pictures of a tumor sample on a pathology slide and identifies previously underappreciated features, such as tumor microheterogeneity, that could help predict whether a tumor will respond to immunotherapy.

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