PTEN and endometrial cancer: To develop a machine learning model integrates multi-parametric magnetic resonance imaging (MRI) radiomics features and clinicopathological features to predict the expression status of phosphatase and tension homolog (PTEN), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), and mammalian target of rapamycin (mTOR), which are frequently linked with targeted therapy for endometrial cancer (EC), in order to establish a dependable foundation for personalized adjuvant therapy for EC patients.