Seoul National University College of Medicine Researcher Updates Current Study Findings on Atrial Fibrillation (Automatic segmentation of atrial fibrillation and flutter in single-lead electrocardiograms by self-supervised learning and...).

Předmět:	ATRIAL flutter ATRIAL fibrillation RESEARCH personnel UNIVERSITIES & colleges ARRHYTHMIA ELECTRONOGRAPHY
Zdroj:	Cardiovascular Week; 11/27/2023, p1265-1265, 1p
Abstrakt:	A recent study conducted by researchers at Seoul National University College of Medicine in South Korea focused on the automatic detection of atrial fibrillation and flutter (AF/AFL) in single-lead electrocardiograms (ECGs) using a deep learning model. The researchers developed a Transformer-based model that was pretrained using masked signal modeling (MSM) and fine-tuned to predict AF/AFL areas. The model achieved high performance in segmenting AF/AFL, with intersection over union (IOU) values of 0.9254 and 0.9477 for AF/AFL segmentation and other segmentation tasks, respectively. The study concluded that the model with self-supervised learning by MSM performed robustly in segmenting AF/AFL. [Extracted from the article]
Databáze:	Complementary Index
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