Development of Machine Learning Models for Predicting Prostate Cancer in Biopsy Candidates Using Prostate‐Specific Antigen, Magnetic Resonance Imaging, and Hematologic Parameters

XGBoost and RF models demonstrated excellent performance, with high AUC values. To generalize the results, it is necessary to confirm the accuracy of ML models through external validation in different populations.