A foundation for evaluating the surgical artificial intelligence literature.

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Published Date: Feb 10, 2024

Abstract

With increasing growth in applications of artificial intelligence (AI) in surgery, it has become essential for surgeons to gain a foundation of knowledge to critically appraise the scientific literature, commercial claims regarding products, and regulatory and legal frameworks that govern the development and use of AI. This guide offers surgeons a framework with which to evaluate manuscripts that incorporate the use of AI. It provides a glossary of common terms, an overview of prerequisite knowledge to maximize understanding of methodology, and recommendations on how to carefully consider each element of a manuscript to assess the quality of the data on which an algorithm was trained, the appropriateness of the methodological approach, the potential for reproducibility of the experiment, and the applicability to surgical practice, including considerations on generalizability and scalability.

Authors

  • Daniel A Hashimoto
    Department of Surgery, Massachusetts General Hospital, Boston, MA.
  • Sai Koushik Sambasastry
    Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.
  • Vivek Singh
  • Sruthi Kurada
    Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.
  • Maria Altieri
    Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Global Surgical AI Collaborative, Toronto, ON, USA.
  • Takuto Yoshida
    Surgical AI Research Academy, Department of Surgery, University Health Network, Toronto, ON, USA.
  • Amin Madani
    Department of Surgery, Columbia University Irving Medical Center, 161 Fort Washington Avenue, New York, NY 10032, USA.
  • Matjaz Jogan
    Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

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