Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis.

Journal: BMC cardiovascular disorders
PMID: 40269704

Abstract

INTRODUCTION: Percutaneous coronary intervention (PCI) has been the main treatment of coronary artery disease (CAD). In this review, we aimed to compare the performance of machine learning (ML) vs. logistic regression (LR) models in predicting different outcomes after PCI.

Authors

  • Sepehr Nayebirad
    Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, 1411713138, Iran.
  • Ali Hassanzadeh
    Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
  • Amir Mohammad Vahdani
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • Aida Mohamadi
    Rheumatology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
  • Shayan Forghani
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • Akbar Shafiee
    Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, 1411713138, Iran. Electronic address: ashafiee@tums.ac.ir.
  • Farzad Masoudkabir
    Department of Cardiology, Tehran Heart Center, Tehran University of Medical Sciences, North Kargar Avenue, Tehran 1411713138, Iran.

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