Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

Journal: BMC cardiovascular disorders
PMID: 39702050

Abstract

INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalies, constitutes a significant contributor to the burden of non-communicable diseases, highlighting the critical need for improved risk assessment tools. Artificial intelligence (AI) holds promise in enhancing outcome predictions for congenital cardiac surgery. This study aims to systematically review the utilization of AI in predicting post-operative outcomes in this population.

Authors

  • Ida Mohammadi
    Farzan Artificial Intelligence Team, Farzan Clinical Research Institute, Tehran, Islamic Republic of Iran.
  • Shahryar Rajai Firouzabadi
    Cardiovascular Surgery Research and Development Committee, Iran University of Medical Sciences (IUMS), PO box 14665-354, Tehran, Iran.
  • Melika Hosseinpour
    Cardiovascular Surgery Research and Development Committee, Iran University of Medical Sciences (IUMS), Tehran, 14665-354, Iran.
  • Mohammadhosein Akhlaghpasand
    Cardiovascular Surgery Research and Development Committee, Iran University of Medical Sciences (IUMS), Tehran, 14665-354, Iran. Akhlaghpasandm@yahoo.com.
  • Bardia Hajikarimloo
    Skull Base Research Center, Loghman-Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Sam Zeraatian-Nejad
    Cardiovascular Surgery Research and Development Committee, Iran University of Medical Sciences (IUMS), Tehran, 14665-354, Iran.
  • Peyman Sardari Nia
    Department of Cardiothoracic Surgery, Maastricht University Medical Centre, Maastricht, Netherlands.

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