Artificial intelligence quantifying endoscopic severity of ulcerative colitis in gradation scale.

Journal: Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
PMID: 37690125

Abstract

OBJECTIVES: Existing endoscopic scores for ulcerative colitis (UC) objectively categorize disease severity based on the presence or absence of endoscopic findings; therefore, it may not reflect the range of clinical severity within each category. However, inflammatory bowel disease (IBD) expert endoscopists categorize the severity and diagnose the overall impression of the degree of inflammation. This study aimed to develop an artificial intelligence (AI) system that can accurately represent the assessment of the endoscopic severity of UC by IBD expert endoscopists.

Authors

  • Kaoru Takabayashi
    Center for Diagnostic and Therapeutic Endoscopy, Keio University School of Medicine, Tokyo, Japan.
  • Taku Kobayashi
    Center for Advanced IBD Research and Treatment, Kitasato University Kitasato Institute Hospital, Tokyo, Japan.
  • Katsuyoshi Matsuoka
    Department of Gastroenterology and Hepatology, Tokyo Medical and Dental University, Tokyo, Japan.
  • Barrett G Levesque
    Division of Gastroenterology, Los Angeles County/University of Southern California Medical Center, Los Angeles, USA.
  • Takuji Kawamura
    Department of Gastroenterology, Kyoto Second Red Cross Hospital, Kyoto, Japan.
  • Kiyohito Tanaka
  • Takeaki Kadota
    Department of Advanced Information Technology, Kyushu University, Fukuoka, Japan.
  • Ryoma Bise
  • Seiichi Uchida
  • Takanori Kanai
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
  • Haruhiko Ogata
    Center for Diagnostic and Therapeutic Endoscopy, Keio University School of Medicine, Tokyo, Japan.

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