Transformer-Based Deep Learning Integrating Multi-Regional MRI and Clinical Features for Predicting Biochemical Recurrence After Radical Prostatectomy: A Multicenter Study

Background

Existing deep learning models for predicting biochemical recurrence (BCR) after radical prostatectomy often ignore the biological context beyond the tumor. This study aims to develop and validate a transformer-based model combining multi-regional magnetic resonance imaging (MRI) features and clinical data to improve BCR prediction after radical prostatectomy in prostate cancer (PCa).