Article

Multicenter self-supervised computational pathology identifies prognostic histomorphological phenotypes in colorectal cancer

2026-07-21

Abstract excerpt

H&E whole-slide images capture prognostic information encoded in tumor morphology and the surrounding microenvironment, but these signals remain difficult to extract and interpret at scale. Here, we developed a self-supervised computational pathology framework to predict disease-free survival in colorectal cancer and link model-derived risk to interpretable histomorphology and spatial tumor biology. Using a multic...

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Literature Corpus work: 0b21fdba-d974-540a-8d7e-2bdd8bddcef4
DOI: 10.64898/2026.07.15.738753

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