Artificial intelligence applications in inflammatory bowel disease: Emerging technologies and future directions.

Content Provider	Europe PMC
Author	Gubatan, John Levitte, Steven Patel, Akshar Balabanis, Tatiana Wei, Mike T Sinha, Sidhartha R
Copyright Year	2021
Abstract	Inflammatory bowel disease (IBD) is a complex and multifaceted disorder of the gastrointestinal tract that is increasing in incidence worldwide and associated with significant morbidity. The rapid accumulation of large datasets from electronic health records, high-definition multi-omics (including genomics, proteomics, transcriptomics, and metagenomics), and imaging modalities (endoscopy and endomicroscopy) have provided powerful tools to unravel novel mechanistic insights and help address unmet clinical needs in IBD. Although the application of artificial intelligence (AI) methods has facilitated the analysis, integration, and interpretation of large datasets in IBD, significant heterogeneity in AI methods, datasets, and clinical outcomes and the need for unbiased prospective validations studies are current barriers to incorporation of AI into clinical practice. The purpose of this review is to summarize the most recent advances in the application of AI and machine learning technologies in the diagnosis and risk prediction, assessment of disease severity, and prediction of clinical outcomes in patients with IBD.
ISSN	10079327
Volume Number	27
PubMed Central reference number	PMC8108036
Issue Number	17
PubMed reference number	34007130
Journal	World Journal of Gastroenterology [World J. Gastroenterol]
e-ISSN	22192840
DOI	10.3748/wjg.v27.i17.1920
Language	English
Publisher	Baishideng Publishing Group Inc
Publisher Date	2021-05-01
Access Restriction	Open
Rights License	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Subject Keyword	Artificial intelligence Machine learning Inflammatory bowel disease Crohn’s disease Ulcerative colitis Clinical outcomes
Content Type	Text
Resource Type	Article
Subject	Gastroenterology