Exploring artificial intelligence methods for cardiac syncope diagnosis combined with electrocardiogram parameters and clinical characteristics.

Journal: Journal of electrocardiology
Published Date: May 7, 2025

Abstract

BACKGROUND: Cardiac syncope can be life-threatening, but there is no clinical tool for initial screening. The study explored and developed optimal artificial intelligence methods for automatic diagnosis of cardiac syncope based on combinations of electrocardiogram parameters and clinical characteristics.

Authors

  • Xiulian Li
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China.
  • Deyun Zhang
    HeartVoice Medical Technology, Hefei, 230027, China.
  • Xinmu Li
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China; Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Xinyi Gao
    Department of Radiology, Zhejiang Cancer Hospital, Hangzhou, China. Electronic address: 10301010213@fudan.edu.cn.
  • Yan Liang
    Department of Chemistry and Biochemistry, The University of Arizona, Tucson, AZ, 85721, United States.
  • Gary Tse
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, 300211 Tianjin, China.
  • Qingpeng Zhang
    Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.
  • Huayue Tao
    The Second Hospital of Tianjin Medical University, Tianjin, China. 85987780@qq.com.
  • Kangyin Chen
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, The Second Hospital of Tianjin Medical University, Tianjin, China. chenkangyin@vip.126.com.
  • Weilun Xu
    HeartVoice Medical Technology, Hefei, China.
  • Guangping Li
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China.
  • Wenling Liu
    Research Institute of Petroleum Exploration & Development, PetroChina, Beijing, China.
  • Gan-Xin Yan
    Lankenau Medical Center, Wynnewood, Pennsylvania, United States of America; Fuwai Huazhong Hospital, Zhengzhou, Henan, China; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.
  • Shenda Hong
    National Institute of Health Data Science at Peking University, Peking University, 100871 Beijing, China.
  • Tong Liu
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.

Keywords

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