Classification of Coronary Artery Disease

The Z-Alizadeh Sani dataset is one of the most common datasets used in machine learning for automatic CAD detection. This dataset contains 303 samples (216 CAD patients and 87 normal) with 55 features. The main features of this dataset are four categories: (1) Demographic, (2) symptoms and examination, (3) electrocardiogram, and (4) laboratory and echo features.

The main advantage of this dataset is its completeness. There are no missing values or outliers in this dataset This dataset is publicly available in the UCI Machine Learning repository for researchers