Predicting operative time for metabolic and bariatric surgery using machine learning models: a retrospective observational study.

Journal: International journal of surgery (London, England)
Published Date: Apr 1, 2024

Abstract

BACKGROUND: Predicting operative time is essential for scheduling surgery and managing the operating room. This study aimed to develop machine learning (ML) models to predict the operative time for metabolic and bariatric surgery (MBS) and to compare each model.

Authors

  • Dong-Won Kang
    Department of Biomedical Engineering, College of Health Science, Yonsei University, Wonju, Kangwon-do, 26493, South Korea.
  • Shouhao Zhou
    Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania.
  • Suman Niranjan
    Department of Logistics and Operations Management, G. Brint Ryan College of Business, University of North Texas, Denton, Texas, USA.
  • Ann Rogers
    Department of Surgery, Penn State College of Medicine.
  • Chan Shen
    Division of Outcomes Research and Quality, Department of Surgery, College of Medicine, Pennsylvania State University, Hershey, PA, USA. Electronic address: cshen@pennstatehealth.psu.edu.

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