Accurate detection of arrhythmias on raw electrocardiogram images: An aggregation attention multi-label model for diagnostic assistance.

Journal: Medical engineering & physics
Published Date: Mar 2, 2023

Abstract

BACKGROUND: The low rate of detection of abnormalities has been a major problem with current artificial intelligence-based electrocardiogram diagnostic algorithms, particularly when applied under real-world clinical scenarios.

Authors

  • Zizhu Liu
    Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China. Electronic address: liuzizhu1996@sjtu.edu.cn.
  • Qing Cao
    Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China. Electronic address: cq30553@rjh.com.cn.
  • Qi Jin
    Department of Ophthalmology, The Affiliated Eye Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
  • Jingsheng Lin
    Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China. Electronic address: jasonlin@rjh.com.cn.
  • Gang Lv
    Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200000, China.
  • Kang Chen
    Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China.

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