Artificial Intelligence Driven Intelligent Computational Model for Heart Disease Prediction: Leveraging Feature Selection

In recent years, heart disease has become a very serious threat to the health and safety of people all over the globe. Typically, this condition occurs when there is an insufficient supply of blood from the heart to various parts of the body, which hampers their usual operations. Early and timely detection of this disease holds paramount importance in preventing patients from further harm and saving their lives. Artificial intelligence (AI) has emerged as a pivotal tool in advancing heart disease prediction through its multifaceted roles. In this study, an intelligent computational model is introduced. This intelligent computational model encompasses multiple stages, including comprehensive data preprocessing and a strategic feature selection process utilizing correlation-based techniques. It also utilizes machine learning and deep neural networks to obtain a robust model for heart disease classification. Serval performance metrics are evaluated to observe the effectiveness of the proposed model. The proposed model achieved the highest classification accuracy of 99.01%. The proposed model contributes a powerful predictive model aimed at enhancing heart disease diagnosis, an imperative step toward effective patient care and potentially life-saving interventions.