Intest Res.  2022 Apr;20(2):165-170. 10.5217/ir.2021.00079.

Artificial intelligence for endoscopy in inflammatory bowel disease

• Takenaka K
• Kawamoto A
• Okamoto R
• Watanabe M
• Ohtsuka K

• KMID: 2529562
• DOI: http://doi.org/10.5217/ir.2021.00079

Abstract

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.

Keyword

Colitis, ulcerative; Crohn disease; Mucosal healing

Figure

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  Fig. 1. Example of a computer-aided diagnosis system. Takenaka et al. [15] constructed a deep neural network to evaluate ulcerative colitis (DNUC) from endoscopic images. This system determined the Ulcerative Colitis Endoscopic Index of Severity (UCEIS) score and histological activity. This figure is published with the permission of the author.

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  Fig. 2. Aspect of artificial intelligence for endoscopy in inflammatory bowel disease. In the future, great advantages are expected for standardized evaluation or disease management.

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