AN EXPLAINABLE MACHINE LEARNING-BASED RISK PREDICTION MODEL FOR IN-HOSPITAL MORTALITY FOR CHINESE STEMI PATIENTS: FINDINGS FROM CHINA MYOCARDIAL INFARCTION REGISTRY

Traditional statistical models usually underestimate the complexity of data, while machine learning models are hard to interpret and are sensitive to the completeness of the input variables. Using data from the China Acute Myocardial Infarction registry, we apply XGBoost machine learning method to