Afreen Karimkhan

This paper develops a self-supervised computational pathology framework to identify prognostic histomorphological phenotypes in colorectal cancer using H&E images and tile embeddings.

This paper uses self-supervised learning to identify histomorphological patterns in colon cancer WSIs, revealing clinically relevant clusters associated with survival and treatment responses.