Bilotta AJ, Trebilcock JA, Hebda NJ, Sasan CK, Cooper KM, Rupawala AH. Artificial intelligence in the management of inflammatory bowel disease: What’s next? World J Gastrointest Pharmacol Ther 2026; 17(1): 112640 [DOI: 10.4292/wjgpt.v17.i1.112640]
Corresponding Author of This Article
Katherine M Cooper, MD, Department of Medicine, UMass Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, United States. katherine.cooper@umassmed.edu
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
World J Gastrointest Pharmacol Ther. Mar 5, 2026; 17(1): 112640 Published online Mar 5, 2026. doi: 10.4292/wjgpt.v17.i1.112640
Artificial intelligence in the management of inflammatory bowel disease: What’s next?
Anthony J Bilotta, Jennifer A Trebilcock, Nicholas J Hebda, Charanpreet K Sasan, Katherine M Cooper, Abbas H Rupawala
Anthony J Bilotta, Jennifer A Trebilcock, Nicholas J Hebda, Charanpreet K Sasan, Katherine M Cooper, Department of Medicine, UMass Chan Medical School, Worcester, MA 01655, United States
Katherine M Cooper, Department of Medicine, Division of Gastroenterology and Hepatology, Massachusetts General Hospital, Boston, MA 02114, United States
Abbas H Rupawala, Department of Medicine, Division of Gastroenterology and Hepatology, UMass Chan Medical School, Worcester, MA 01655, United States
Co-corresponding authors: Katherine M Cooper and Abbas H Rupawala.
Author contributions: Bilotta AJ revised the manuscript; Bilotta AJ and Rupawala AH conceptualized and designed the review; Bilotta AJ, Trebilcock JA, Hebda NJ, and Sasan CK performed the literature search; Bilotta AJ, Trebilcock JA, Hebda NJ, Sasan CK, and Cooper KM interpreted the data and drafted the manuscript; Bilotta AJ, Trebilcock JA, and Hebda NJ created the figures; Cooper KM and Rupawala AH provided critical revisions, they contributed equally to this article, they are the co-corresponding authors of this manuscript; and all authors have read and approved the final manuscript.
Conflict-of-interest statement: Dr. Rupawala reports personal fees from Abbvie, personal fees from Pfizer, personal fees from Takeda, personal fees from BMS, outside the submitted work. All other authors have no conflicts to disclose.
Open Access: 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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Katherine M Cooper, MD, Department of Medicine, UMass Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, United States. katherine.cooper@umassmed.edu
Received: August 4, 2025 Revised: August 24, 2025 Accepted: December 3, 2025 Published online: March 5, 2026 Processing time: 194 Days and 1.5 Hours
Abstract
Inflammatory bowel disease (IBD) is a chronic, relapsing-remitting autoimmune disorder of the gastrointestinal tract. The management of IBD is complex and requires accurate assessment of disease extent and severity which guide therapeutic decisions. Endoscopic evaluation with biopsy remains the standard for diagnosing and assessing disease activity. Additionally, other modalities such as computed tomography enterography are used for suspected small bowel involvement. However, these processes are costly, time consuming, and often rely on subjective interpretation which is influenced by clinician experience. Artificial intelligence (AI) has been used to standardize and improve efficiency in many facets of healthcare. Similarly, in the past decade, there has been growing interest in the applications of AI in the management of IBD. The applications of AI in IBD to date include automated endoscopic and histologic assessment, analysis of non-invasive imaging, discovery of novel biomarkers for the development of disease prediction models and the use of chatbots. In this article, we will discuss recent advancements in the use of AI in IBD as well as some of the practical and ethical concerns with large scale implementation of AI into clinical practice.
Core Tip: Inflammatory bowel disease (IBD) is a chronic relapsing-remitting autoimmune disorder of the gastrointestinal tract. The management of IBD is complex and relies on subjective interpretation of invasive and non-invasive assessments to guide therapeutic decisions. Artificial intelligence (AI) is emerging as a potential tool to standardize the assessment of IBD and personalize therapeutic selection. This article highlights recent advances in AI in IBD with a focus on endoscopy, non-invasive imaging, histology, AI chatbots, therapeutic prediction models and current barriers to widespread implementation of AI in clinical practice.
