Isfara Islam Roza

Abstract Heart disease, a leading cause of death worldwide, accounts for 31% of global fatalities and requires effective early detection methods to combat its rising prevalence. Early detection and prediction of heart disease remain one of the most pressing challenges in current healthcare. In recent years, machine learning (ML) technologies have offered opportunities to address these inequities by improving heart disease detection and prediction capabilities.