Maito Suzuki

Beyond predictive performance: Interpretability challenges and feature importance bias in XGBoost-based readmission models.

Critical limitations in the interpretability and methodological robustness of tree-based algorithms for predicting 1-year unplanned readmissions among elderly patients with coronary heart disease are examined.