Artificial Intelligence, Machine Learning, and Surgical Science: Reality Versus Hype.

Journal: The Journal of surgical research
Published Date: Mar 18, 2021

Abstract

Artificial intelligence (AI) has made increasing inroads in clinical medicine. In surgery, machine learning-based algorithms are being studied for use as decision aids in risk prediction and even for intraoperative applications, including image recognition and video analysis. While AI has great promise in surgery, these algorithms come with a series of potential pitfalls that cannot be ignored as hospital systems and surgeons consider implementing these technologies. The aim of this review is to discuss the progress, promise, and pitfalls of AI in surgery.

Authors

  • Majed El Hechi
    Division of Trauma, Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital, Boston, Massachusetts.
  • Thomas M Ward
    Surgical AI & Innovation Laboratory, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, 15 Parkman Street, WAC460, Boston, MA 02114, USA.
  • Gary C An
    Division of Acute Care Surgery, Department of Surgery, Robert Larner, MD College of Medicine, University of Vermont, Burlington, Vermont.
  • Lydia R Maurer
    Department of Surgery, Massachusetts General Hospital, Boston, MA.
  • Mohamad El Moheb
    Division of Trauma, Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital, Boston, Massachusetts.
  • Georgios Tsoulfas
    Department of Surgery, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • Haytham M Kaafarani
    Division of Trauma, Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital, Boston, Massachusetts. Electronic address: HKAAFARANI@mgh.harvard.edu.

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