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This study proposes an Artificial Intelligence (AI)-based model, namely Integrating Feature Reduction Models for Heart Disease Prediction (IFRM-HDP), which combines a hybrid feature selection strategy incorporating Boruta and minimum Redundancy Maximum Relevance with a Temporal Convolutional Network to capture complex dependencies among clinical attributes and improve classification performance.