Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review.

Journal: Journal of medical Internet research
PMID: 39928932

Abstract

BACKGROUND: Although catheter ablation (CA) is currently the most effective clinical treatment for atrial fibrillation, its variable therapeutic effects among different patients present numerous problems. Machine learning (ML) shows promising potential in optimizing the management and clinical outcomes of patients undergoing atrial fibrillation CA (AFCA).

Authors

  • Aijing Luo
    The Second Xiangya Hospital of Central South University, No. 139, Renmin Road Central, Changsha, Hunan, China.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.
  • Hongtao Zhu
    Shanghai University, Shanghai, 200444, China.
  • Wenzhao Xie
    College of Bioengineering, Chongqing University, Chongqing, 400044, China.
  • Xi Chen
    Department of Critical care medicine, Shenzhen Hospital, Southern Medical University, Guangdong, Shenzhen, China.
  • Zhenjiang Liu
    The Second Xiangya Hospital, Central South University, Changsha, China.
  • Zirui Xin
    The Second Xiangya Hospital, Central South University, Changsha, China.

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