Developing a novel framework using optimized active stacking and explainable AI for heart disease prediction

doi:10.1016/j.cmpb.2025.109169

Developing a novel framework using optimized active stacking and explainable AI for heart disease prediction

2025-11-17

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Abdul Khader Jilani Saudagar

D

Dragan Pamucar

DOI：10.1016/j.cmpb.2025.109169

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• We use PCA for dimension reduction. • ProWRAS is employed to address class imbalance. • Proposed staking model, OSM-BO, and EAL-OSM for heart disease prediction. • 10-FCV is applied to validate the proposed model’s results. • XAI techniques: SHAP and LIME explain each feature’s contribution in classification.

Developing a novel framework using optimized active stacking and explainable AI for heart disease prediction

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