A machine learning–driven and explainable prediction model for in-hospital mortality in patients with diabetes mellitus and congestive heart failure: integrating XGBoost and SHAP approaches
Patients with congestive heart failure (CHF) and type 2 diabetes mellitus (T2DM) are at elevated risk of in-hospital mortality, particularly in intensive care units (ICUs). Conventional scoring systems may not fully capture the clinical complexity of such comorbidities. This study aimed to construct an interpretabl...