AI RESEARCH
Deep Learning From Routine Histology Improves Risk Stratification for Biochemical Recurrence in Prostate Cancer
arXiv CS.CV
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ArXi:2603.14187v1 Announce Type: new Accurate prediction of biochemical recurrence (BCR) after radical prostatectomy is critical for guiding adjuvant treatment and surveillance decisions in prostate cancer. However, existing clinicopathological risk models reduce complex morphology to relatively coarse descriptors, leaving substantial prognostic information embedded in routine histopathology underexplored. We present a deep learning-based biomarker that predicts continuous, patient-specific risk of BCR directly from H&E-stained whole-slide prostatectomy specimens.