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Artificial intelligence-assisted colonoscopy to identify histologic remission and predict the outcomes of patients with ulcerative colitis: A systematic review.
Maeda, Yasuharu; Kudo, Shin-Ei; Santacroce, Giovanni; Ogata, Noriyuki; Misawa, Masashi; Iacucci, Marietta.
Afiliação
  • Maeda Y; Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan; APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, T12 YT20, Ireland. Electronic address: yasuharu@med.showa-u.ac.jp.
  • Kudo SE; Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan.
  • Santacroce G; APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, T12 YT20, Ireland.
  • Ogata N; Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan.
  • Misawa M; Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan.
  • Iacucci M; APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, T12 YT20, Ireland.
Dig Liver Dis ; 56(7): 1119-1125, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38643020
ABSTRACT
This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of patients with ulcerative colitis. The use of artificial intelligence (AI) has increased substantially across several medical fields, including gastrointestinal endoscopy. Evidence suggests that it may be helpful to predict histologic remission and relapse, which would be beneficial because current histological diagnosis is limited by the inconvenience of obtaining biopsies and the high cost and time-intensiveness of pathological diagnosis. MEDLINE and the Cochrane Central Register of Controlled Trials were searched for studies published between January 1, 2000, and October 31, 2023. Nine studies fulfilled the selection criteria and were included; five evaluated the prediction of histologic remission, two assessed the prediction of clinical outcomes, and two evaluated both. Seven were prospective observational or cohort studies, while two were retrospective observational studies. No randomized controlled trials were identified. AI-assisted colonoscopy demonstrated sensitivity between 65 %-98 % and specificity values of 80 %-97 % for identifying histologic remission. Furthermore, it was able to predict future relapse in patients with ulcerative colitis. However, several challenges and barriers still exist to its routine clinical application, which should be overcome before the true potential of AI-assisted colonoscopy can be fully realized.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Colite Ulcerativa / Colonoscopia Limite: Humans Idioma: En Revista: Dig Liver Dis Assunto da revista: GASTROENTEROLOGIA Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Colite Ulcerativa / Colonoscopia Limite: Humans Idioma: En Revista: Dig Liver Dis Assunto da revista: GASTROENTEROLOGIA Ano de publicação: 2024 Tipo de documento: Article