Utilizing Machine Learning to Classify Type of Heartbeat in Athletes from Electrocardiogram Data
This study presents a machine learning framework that utilizes a weighted ensemble of deep learning models to accurately classify athlete heartbeats from ECG data, achieving high performance in distinguishing normal, supraventricular, and ventricular ectopic beats to support scalable cardiac screening.