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Abstract: Heart disease remains a leading cause of morbidity and mortality worldwide. Early detection and accurate prediction of heart disease risk factors are crucial for effective prevention and timely intervention. In recent years, machine learning techniques have emerged as powerful tools for predictive analytics in healthcare. This paper presents a comprehensive review of recent advances in the application of machine learning algorithms for heart disease prediction. The review begins by discussing the significance of heart disease prediction and the limitations of traditional risk assessment methods.
Ms. Komal S. Bansode (Mon,) studied this question.