Application of Artificial Intelligence to Clinical Practice in Inflammatory Bowel Disease – What the Clinician Needs to Know

Abstract Artificial intelligence [AI] techniques are quickly spreading across medicine as an analytical method to tackle challenging clinical questions. What were previously thought of as highly complex data sources, such as images or free text, are now becoming manageable. Novel analytical methods...

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Bibliographic Details
Published in:Journal of Crohn's and colitis 2022-03, Vol.16 (3), p.460-471
Main Authors: Chen, David, Fulmer, Clifton, Gordon, Ilyssa O, Syed, Sana, Stidham, Ryan W, Vande Casteele, Niels, Qin, Yi, Falloon, Katherine, Cohen, Benjamin L, Wyllie, Robert, Rieder, Florian
Format: Article
Language:English
Subjects:
Artificial Intelligence
Chronic Disease
Colitis
Diagnostic Imaging
Humans
Inflammatory Bowel Diseases - diagnosis
Inflammatory Bowel Diseases - therapy
Review
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Summary:Abstract Artificial intelligence [AI] techniques are quickly spreading across medicine as an analytical method to tackle challenging clinical questions. What were previously thought of as highly complex data sources, such as images or free text, are now becoming manageable. Novel analytical methods merge the latest developments in information technology infrastructure with advances in computer science. Once primarily associated with Silicon Valley, AI techniques are now making their way into medicine, including in the field of inflammatory bowel diseases [IBD]. Understanding potential applications and limitations of these techniques can be difficult, in particular for busy clinicians. In this article, we explain the basic terminologies and provide a particular focus on the foundations behind state-of-the-art AI methodologies in both imaging and text. We explore the growing applications of AI in medicine, with a specific focus on IBD to inform the practising gastroenterologist and IBD specialist. Finally, we outline possible future uses of these technologies in daily clinical practice.
ISSN:1873-9946
1876-4479
DOI:10.1093/ecco-jcc/jjab169