Feature Correlation and Importance Analysis for Heart Attack Prediction - Negi, Paras; Bisht, Manoj Kumar (Indian Journal of Computer Science, 2025)
Cardiovascular diseases are a leading cause of global mortality, with heart attacks being a major contributor. Early detection and accurate risk evaluation are essential for reducing adverse outcomes. This study analysed a publicly available heart attack dataset to identify significant predictors of heart attack. We examined relationships between the target variable (heart attack/no heart attack) and clinical features. The findings offered insights for developing accurate and interpretable predictive models, supporting early diagnosis and improved clinical decision-making.