Santi Santi

Performance Comparison of Tree-Based Models for Heart Disease Prediction Using Feature Selection and SMOTE

The findings demonstrate that the proposed integration of oversampling, feature selection, and threshold optimization can improve predictive performance for imbalanced cardiovascular risk data, providing a practical foundation for machine learning–based decision support in early heart disease risk screening.