A Novel Hybrid Stacked Ensemble Model with XAI for Robust and Interpretable HIV Infection Prediction

A stacked ensemble model integrating five heterogeneous classifiers with logistic regression as meta-learner. The framework incorporates Z-score normalization and SMOTE, achieving AUC of 0.711 and recall of 0.748. SHAP-based interpretability reveals key contributing features for clinical adoption.