Leveraging artificial intelligence for predicting spontaneous closure of perimembranous ventricular septal defect in children: a multicentre, retrospective study in China.

Journal: The Lancet. Digital health
Published Date: Jan 1, 2025

Abstract

BACKGROUND: Perimembranous ventricular septal defect (PMVSD) is a prevalent congenital heart disease, presenting challenges in predicting spontaneous closure, which is crucial for therapeutic decisions. Existing models mainly rely on structured echocardiographic parameters or restricted data. This study introduces an artificial intelligence (AI)-based model, which uses natural language processing (NLP) and machine learning with the aim of improving spontaneous closure predictability in PMVSD.

Authors

  • Jing Sun
    Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Tienan Feng
    Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Bo Wang
    Department of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People's Hospital, Hohhot, Inner Mongolia, China.
  • Fen Li
    College of Information Science and Engineering, Hunan University, 2 Lushan S Rd, Yuelu District, 410086, Changsha, China.
  • Bo Han
    Faculty of Material Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China.
  • Maoping Chu
    Department of Pediatric Cardiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
  • Fangqi Gong
    Department of Pediatric Cardiology, Children's Hospital affiliated with Zhejiang University School of Medicine, Hangzhou, China.
  • Qijian Yi
    Department of Pediatric Cardiology, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • Xin Zhou
    School of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, China.
  • Sun Chen
    Department of Pediatric Cardiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Engineering Research Center of Techniques and Instruments for Diagnosis and Treatment of Congenital Heart Disease, Ministry of Education, Shanghai, China.
  • Xin Sun
    Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA.
  • Kun Sun

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