Artificial intelligence for the assessment of bowel preparation.

Journal: Gastrointestinal endoscopy
PMID: 34896100

Abstract

BACKGROUND AND AIMS: A reliable assessment of bowel preparation is important to ensure high-quality colonoscopy. Current bowel preparation scoring systems are limited by interobserver variability. This study aimed to demonstrate objective assessment of bowel preparation adequacy using an artificial intelligence (AI)/convolutional neural network (CNN) algorithm developed from colonoscopy videos.

Authors

  • Ji Young Lee
  • Audrey H Calderwood
    Department of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA; The Geisel School of Medicine at Dartmouth and the Dartmouth Institute of Health Policy and Clinical Practice, Hanover, New Hampshire, USA.
  • William Karnes
    Department of Medicine, University of California, Irvine, California; H.H. Chao Comprehensive Digestive Disease Center, University of California, Irvine, California.
  • James Requa
    Docbot Inc, Irvine, California, USA.
  • Brian C Jacobson
    Department of Medicine, Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Michael B Wallace

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