Automatic assessment of bowel preparation by an artificial intelligence model and its clinical applicability.

Journal: Journal of gastroenterology and hepatology
PMID:

Abstract

BACKGROUND AND AIM: Reliable bowel preparation assessment is important in colonoscopy. However, current scoring systems are limited by laborious and time-consuming tasks and interobserver variability. We aimed to develop an artificial intelligence (AI) model to assess bowel cleanliness and evaluate its clinical applicability.

Authors

  • Ji Young Lee
  • Jooyoung Park
    Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Hyo Jeong Lee
    Health Screening Promotion Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Hana Park
    Health Screening Promotion Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Eun Hyo Jin
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Kanggil Park
    Department of Convergence Medicine, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Ji Eun Baek
    Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Dong-Hoon Yang
    Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Seung Wook Hong
    Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Namkug Kim
    Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Jeong-Sik Byeon
    Department of Gastroenterology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea. jsbyeon@amc.seoul.kr.