Therefore, this study aims to develop and validate an interpretable machine learning model for the non-invasive prediction of HER2 overexpression in prostate cancer by integrating radiomic features derived from biparametric MRI with clinical variables. The gene discussed is ERBB2; the disease is prostate carcinoma.