Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease

BackgroundThe diagnostic power of exercise stress electrocardiography (ExECG) remains limited. We aimed to construct an artificial intelligence (AI)-based method to enhance ExECG performance to identify patients with significant coronary artery disease (CAD).MethodsWe retrospectively collected 818 p...

Full description

Saved in:

Bibliographic Details
Main Authors:	Hsin-Yueh Liang, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-03-01
Series:	Frontiers in Artificial Intelligence
Subjects:	exercise stress electrocardiography coronary artery disease deep learning multimodal approach feature variable artificial intelligence
Online Access:	https://www.frontiersin.org/articles/10.3389/frai.2025.1496109/full
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease

Similar Items