ECG-Based Unsupervised Clustering in Coronary Artery Disease Associates with Ventricular Arrhythmia

Abstract

Coronary Artery Disease (CAD) is a leading cause of life-threatening ventricular arrhythmias (LTVAs). This study aimed to identify distinct clusters of CAD individuals based on QRS morphology using a 3-nearest neighbors clustering algorithm. Cluster 1, characterized by the lowest QRS amplitudes and widest QRS complexes, was strongly associated with LTVA risk.