Explainable Graph Convolutional Network Framework for Robust ECG Arrhythmia Classification and Patient-Level Risk Stratification
Accurate and interpretable detection of arrhythmias from electrocardiogram (ECG) signals plays a critical role in the early cardiac risk assessment and patient management. This paper presents a novel, explainable framework that leverages a dynamic Graph Convolutional Network (GCN) to model ECG beat sequences as graphs,...