This study focuses on the application of machine learning methods for predicting cardiac diseases, aiming to develop accurate and interpretable diagnostic models. The primary objective is to enhance prediction accuracy and identify key risk factors. Various classification algorithms, including Random Forest, Gradient Boosting, Support Vector Machines (SVM), and Neural ...