Confidence-based classification of clinically significant prostate cancer on biparametric MRI using Monte Carlo dropout and Grad-CAM visualization

Objective

Accurate early diagnosis of Clinically Significant prostate cancer (csPCa) is crucial for improving patient survival rates. This study aimed to develop and validate an interpretable, confidence-based deep learning model for csPCa classification using biparametric MRI (bpMRI).

Methods