Amirhossein Ravari

RHYTHMBERT: A SELF-SUPERVISED LANGUAGE MODEL BASED ON LATENT REPRESENTATIONS OF ECG WAVEFORMS FOR HEART DISEASE DETECTION

Electrocardiogram (ECG) analysis is crucial for diagnosing heart disease, but most self-supervised learning methods treat ECG as a generic time series, overlooking physiologic semantics and rhythm-level structure. Existing contrastive methods utilize augmentations that distort morphology, whereas ge…