Prediction of hospital mortality in sepsis-associated acute kidney injury using a machine-learning approach: a multicenter study using SHAP interpretability analysis

The interpretable machine learning model demonstrated excellent performance and robust generalizability for S-AKI mortality prediction across five international databases. SHAP analysis provided clinically meaningful insights supporting personalized risk stratification and evidence-based clinical decision-making.