Application of machine learning in predicting postoperative arrhythmia following transcatheter closure of perimembranous ventricular septal defects.

Journal: Kardiologia polska
PMID: 39743914

Abstract

BACKGROUND: Arrhythmia is a frequent complication following transcatheter device closure of perimembranous ventricular septal defects (pmVSD). However, there is currently a lack of a convenient tool for predicting postoperative arrhythmia.

Authors

  • Lintao Yan
    Department of Pediatric Cardiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
  • Yuan Meng
    State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China.
  • Hongjie Sun
    College of Computer Science and Technology, Qingdao University, Qingdao, 266071, Shandong, China.
  • Xinlei Liu
    College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, P. R. China.
  • Bo Han
    Faculty of Material Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China.

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