Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.

Journal: Gastrointestinal endoscopy
Published Date:

Abstract

In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In this article, we provide a guiding framework for all stakeholders in the endoscopy AI ecosystem regarding the standards, metrics, and evaluation methods for emerging and existing AI applications to aid in their clinical adoption and implementation. We also provide guidance and best practices for evaluation of AI technologies as they mature in the endoscopy space. Note, this is a living document; periodic updates will be published as progress is made and applications evolve in the field of AI in endoscopy.

Authors

  • Sravanthi Parasa
    Department of Gastroenterology, Swedish Medical Center, Seattle, Washington, USA.
  • Alessandro Repici
    Digestive Endoscopy Unit, Division of Gastroenterology, Humanitas Clinical and Research Center IRCCS, Rozzano, 20089, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, MI, Italy.
  • Tyler Berzin
    Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
  • Cadman Leggett
    Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA.
  • Seth A Gross
    Division of Gastroenterology and Hepatology, NYU Langone Health, New York, New York, USA.
  • Prateek Sharma
    Department of Gastroenterology and Hepatology, Kansas City VA Medical Center, Kansas City, Kansas, USA.