An explainable AI-driven hybrid feature selection approach for coronary artery disease diagnosis.

The first two techniques yield subsets of highly significant and top-ranked features, which are subsequently evaluated using nine ML algorithms—AdaBoost, KNN, LR, SVM, classification-via-clustering, Boosted Regression Tree (BRT), Stochastic Gradient Boosting (SGB), RF, and NB.

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