At present, machine learning (ML) models have been extensively employed in various healthcare aspects, including disease prevention, diagnosis, treatment, and prognosis prediction—such as disease risk prediction, patient readmission prediction, death prediction, and patient care need prediction—delivering commendable results. The primary objectives of implementing ML in clinical medicine encompass (i) delivering precise predictions and judgments for predictive tasks and (ii) utilizing trained models to guide clinical practice and research.