AI-Based Prediction of Androgen Receptor Expression and Its Prognostic Significance in Prostate Cancer

Abstract Biochemical recurrence (BCR) of prostate cancer (PCa) negatively impacts patients’ post-surgery quality of life, while traditional predictive models show limited accuracy. This study developed an AI-based prognostic model using deep learning, incorporating androgen receptor (AR) regional features from whole slide images (WSIs). Data from 545 patients across two centers were used for training and validation. The model showed strong performance, with high accuracy in AR high-expression region identification and BCR prediction. This AI model may help identify high-risk patients, aiding in better treatment strategies, particularly in underdeveloped areas.