Article

Phenotypic and prognostic insights through unbiased self-supervised learning on kidney histology

2025-06-10

Abstract excerpt

Deep learning methods for image segmentation and classification in histopathology generally utilize supervised learning, relying on manually created labels for model development. Here, we applied a self-supervised framework to characterize kidney histology without the use of pathologist annotations, training on whole slide images to identify histomorphological phenotype clusters (HPCs) and create slide-level vecto...

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Literature Corpus work: cba023d1-370b-59c0-803d-46cfca0a3a7d
DOI: 10.1101/2025.06.09.25328891

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