AI Pathology Model Predicts Breast Cancer Recurrence Risk from H&E Slides
kjgeras · x · 2026-07-06
Researchers shared an AI breast cancer prognostic prediction test: inputs include standard H&E pathology slides plus clinical variables (age, T/N stage, ER/PR/HER2, histology type). The Kestrel foundation model extracts morphological features, and a survival model fuses pathology and clinical signals to output a final 0-1 risk score. Requiring no additional tissue processing or gene sequencing, it runs directly on core biopsy specimens to support earlier risk assessment.
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