The aim of this study was to evaluate the effectiveness of a machine learning model combining clinicopathological features and multi-parametric MRI-based radiomics features in predicting the expression of common endometrial cancer targeted therapy-related proteins PTEN, PIK3CA and mTOR, and to assist in clinical decision-making to optimize personalized treatment for EC patients. The gene discussed is PTEN; the disease is endometrial cancer.