RawECGNet: Deep Learning Generalization for Atrial Fibrillation Detection From the Raw ECG.
Journal:
IEEE journal of biomedical and health informatics
Published Date:
Sep 5, 2024
Abstract
INTRODUCTION: Deep learning models for detecting episodes of atrial fibrillation (AF) using rhythm information in long-term ambulatory ECG recordings have shown high performance. However, the rhythm-based approach does not take advantage of the morphological information conveyed by the different ECG waveforms, particularly the f-waves. As a result, the performance of such models may be inherently limited.