Deep Learning-based 12-Lead Electrocardiogram for Low Left Ventricular Ejection Fraction Detection in Patients.

Journal: The Canadian journal of cardiology
PMID: 39343388

Abstract

BACKGROUND: Reduced left ventricular ejection fraction (LVEF) initiates heart failure, and promptly identifying low ejection fraction is crucial for managing progression and averting mortality. In this study we developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm to identify patients with low ejection fraction and predict LVEF values.

Authors

  • Yuxin Hou
    School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China. Electronic address: 10173662@cumt.edu.cn.
  • Zhiping Fan
    College of Medical Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China.
  • Jiaqi Li
    Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People's Republic of China.
  • Zi Zeng
    Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Gang Lv
    Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200000, China.
  • Jingsheng Lin
    Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China. Electronic address: jasonlin@rjh.com.cn.
  • Liang Zhou
    Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China. liang.zhou@fdeent.org.
  • Tao Wu
    Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China.
  • Qing Cao
    Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China. Electronic address: cq30553@rjh.com.cn.

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