MACHINE LEARNING-BASED PREDICTION OF HEART FAILURE MORTALITY USING CLINICAL BIOMARKERS AND IMBALANCED DATA STRATEGIES
It is demonstrated that machine learning models can effectively identify high-risk patients and that minority data resampling significantly improves mortality classification reliability, and the approach offers potential value for clinical decision support systems and prioritised care pathways.