Explainable SHAP-XGBoost models for in-hospital mortality after myocardial infarction

Abstract

The literature lacks explainable ML models predicting in-hospital mortality after an MI. In a national registry, explainable ML models performed best in ruling out in-hospital death post-MI, and their explanation illustrated their potential for guiding hypothesis generation and future study design.