Explainable Artificial Intelligence for Tabular Data in Healthcare: A Systematic Review of Methods, Evaluation, and Applications
This systematic review provides a comprehensive analysis of XAI methods specifically applied to tabular healthcare data for classification tasks, revealing that SHAP remains the dominant post-hoc method, achieving strong model fidelity but showing inconsistent alignment with clinical expert reasoning.