HXAI-ML: A hybrid explainable artificial intelligence based machine learning model for cardiovascular heart disease detection

Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality globally. Early diagnosis and accurate prediction are critical for effective prevention and treatment. However, traditional machine learning (ML) models for CVD prediction face challenges such as data imbalance, lack of interpretability, and limited generalization across datasets, which restrict their practical application in healthcare. This study introduces a hybrid explainable artificial intelligence-based ML (HXAI-ML) model to address these limitations. The proposed framework combines advanced data balancing techniques, including Random Oversampling (RO), Synthetic Minority Oversampling Technique (SM), RO+Tomek Link (TL), SM+TL,…

• KS
  King Saud University