Article

Deep Learning Predicts Survival Across Squamous Tumor Entities From H&E Stains: Insights from Head and Neck, Esophagus, Lung and Cervical Cancer

2025-04-05

Abstract excerpt

Computational pathology-based models are becoming increasingly popular for extracting biomarkers from images of cancer tissue. However, their validity is often only demonstrated on a single unseen validation cohort, limiting insights into their generalizability and posing challenges for explainability. In this study, we developed models to predict overall survival using haematoxylin and eosin (H&E) slides from FFP...

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Literature Corpus work: ac2c6d9b-f2be-5e31-b372-cc5378e8d85e
DOI: 10.1101/2025.03.31.646351

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Deep Learning Predicts Survival Across Squamous Tumor Entities From H&E Stains: Insights from Head and Neck, Esophagus, Lung and Cervical CancerDOI 10.1101/2025.03.31.646351Read

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