An artificial intelligence-enabled electrocardiogram algorithm for the prediction of left atrial low-voltage areas in persistent atrial fibrillation.

Journal: Journal of cardiovascular electrophysiology
PMID: 39054663

Abstract

OBJECTIVES: We aimed to construct an artificial intelligence-enabled electrocardiogram (ECG) algorithm that can accurately predict the presence of left atrial low-voltage areas (LVAs) in patients with persistent atrial fibrillation.

Authors

  • Yirao Tao
    Department of Cardiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
  • Deyun Zhang
    HeartVoice Medical Technology, Hefei, 230027, China.
  • Chen Tan
    Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China (R.W., L.W., C.T., J.X., J.F.). Electronic address: 18510247762@163.com.
  • Yanjiang Wang
    Department of Cardiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
  • Liang Shi
    Department of Andrology,Drum Tower Clinical College of Nanjing Medical University，Nanjing, jiangsu 210008,China.
  • Hongjie Chi
    Department of Cardiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
  • Shijia Geng
    HeartVoice Medical Technology, Hefei, 230027, China.
  • Zhimin Ma
    Department of Cardiology, Heart Rhythm Cardiovascular Hospital, Shandong, China.
  • Shenda Hong
    National Institute of Health Data Science at Peking University, Peking University, 100871 Beijing, China.
  • Xing Peng Liu
    Department of Cardiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.

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