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Artificial intelligence for endoscopy in inflammatory bowel disease

Inflammatory bowel disease (IBD), with its 2 subtypes, Crohn’s disease and ulcerative colitis, is a complex chronic condition. A precise definition of disease activity and appropriate drug management greatly improve the clinical course while minimizing the risk or cost. Artificial intelligence (AI)...

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Detalles Bibliográficos
Autores principales: Takenaka, Kento, Kawamoto, Ami, Okamoto, Ryuichi, Watanabe, Mamoru, Ohtsuka, Kazuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Association for the Study of Intestinal Diseases 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9081991/
https://www.ncbi.nlm.nih.gov/pubmed/34986607
http://dx.doi.org/10.5217/ir.2021.00079
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author Takenaka, Kento
Kawamoto, Ami
Okamoto, Ryuichi
Watanabe, Mamoru
Ohtsuka, Kazuo
author_facet Takenaka, Kento
Kawamoto, Ami
Okamoto, Ryuichi
Watanabe, Mamoru
Ohtsuka, Kazuo
author_sort Takenaka, Kento
collection PubMed
description Inflammatory bowel disease (IBD), with its 2 subtypes, Crohn’s disease and ulcerative colitis, is a complex chronic condition. A precise definition of disease activity and appropriate drug management greatly improve the clinical course while minimizing the risk or cost. Artificial intelligence (AI) has been used in several medical diseases or situations. Herein, we provide an overview of AI for endoscopy in IBD. We discuss how AI can improve clinical practice and how some components have already begun to shape our knowledge. There may be a time when we can use AI in clinical practice. As AI systems contribute to the exact diagnosis and treatment of human disease, we should continue to learn best practices in health care in the field of IBD.
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spelling pubmed-90819912022-05-17 Artificial intelligence for endoscopy in inflammatory bowel disease Takenaka, Kento Kawamoto, Ami Okamoto, Ryuichi Watanabe, Mamoru Ohtsuka, Kazuo Intest Res Review Inflammatory bowel disease (IBD), with its 2 subtypes, Crohn’s disease and ulcerative colitis, is a complex chronic condition. A precise definition of disease activity and appropriate drug management greatly improve the clinical course while minimizing the risk or cost. Artificial intelligence (AI) has been used in several medical diseases or situations. Herein, we provide an overview of AI for endoscopy in IBD. We discuss how AI can improve clinical practice and how some components have already begun to shape our knowledge. There may be a time when we can use AI in clinical practice. As AI systems contribute to the exact diagnosis and treatment of human disease, we should continue to learn best practices in health care in the field of IBD. Korean Association for the Study of Intestinal Diseases 2022-04 2022-01-07 /pmc/articles/PMC9081991/ /pubmed/34986607 http://dx.doi.org/10.5217/ir.2021.00079 Text en © Copyright 2022. Korean Association for the Study of Intestinal Diseases. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Takenaka, Kento
Kawamoto, Ami
Okamoto, Ryuichi
Watanabe, Mamoru
Ohtsuka, Kazuo
Artificial intelligence for endoscopy in inflammatory bowel disease
title Artificial intelligence for endoscopy in inflammatory bowel disease
title_full Artificial intelligence for endoscopy in inflammatory bowel disease
title_fullStr Artificial intelligence for endoscopy in inflammatory bowel disease
title_full_unstemmed Artificial intelligence for endoscopy in inflammatory bowel disease
title_short Artificial intelligence for endoscopy in inflammatory bowel disease
title_sort artificial intelligence for endoscopy in inflammatory bowel disease
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9081991/
https://www.ncbi.nlm.nih.gov/pubmed/34986607
http://dx.doi.org/10.5217/ir.2021.00079
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