Minea H, Singeap AM, Minea M, Chiriac S, Stanciu C, Trifan A. Artificial intelligence in inflammatory bowel disease: Current applications and future directions. World J Gastroenterol 2025; 31(39): 111353 [DOI: 10.3748/wjg.v31.i39.111353]
Corresponding Author of This Article
Stefan Chiriac, MD, Lecturer, Department of Gastroenterology, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, Bd. Independentei 1, Iasi 700115, Romania. stefannchiriac@yahoo.com
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 Gastroenterol. Oct 21, 2025; 31(39): 111353 Published online Oct 21, 2025. doi: 10.3748/wjg.v31.i39.111353
Artificial intelligence in inflammatory bowel disease: Current applications and future directions
Horia Minea, Ana-Maria Singeap, Manuela Minea, Stefan Chiriac, Carol Stanciu, Anca Trifan
Horia Minea, Ana-Maria Singeap, Stefan Chiriac, Carol Stanciu, Anca Trifan, Department of Gastroenterology, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, Iasi 700115, Romania
Manuela Minea, Department of Microbiology, The National Institute of Public Health, Iasi 700464, Romania
Author contributions: Trifan A designed the review; Minea H, Minea M and Chiriac S wrote the paper; Singeap AM and Stanciu C revised the paper; All authors read and approved the final manuscript.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
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: Stefan Chiriac, MD, Lecturer, Department of Gastroenterology, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, Bd. Independentei 1, Iasi 700115, Romania. stefannchiriac@yahoo.com
Received: June 30, 2025 Revised: August 10, 2025 Accepted: September 15, 2025 Published online: October 21, 2025 Processing time: 115 Days and 19.7 Hours
Abstract
Inflammatory bowel disease (IBD) represents a major global health concern, significantly impacting patient quality of life and healthcare systems. Mucosal and histological healing have emerged as key therapeutic targets, offering better long-term outcomes compared with previous targets. However, accurate disease assessment remains challenging because of interobserver variability and inconsistencies between endoscopic and histological findings. Artificial intelligence (AI) is transforming IBD care by enhancing the precision and reproducibility of disease evaluation. This review provided a structured synthesis of AI applications in IBD, organized by diagnostic, histological, and therapeutic domains, and highlighted comparative model performance such as machine learning classifiers (random forest, support vector machine) and deep learning models (convolutional and recurrent neural networks) with reported accuracy between 80% and 97% and areas under the curve ranging from 0.74 to 0.99. Beyond summarizing existing tools, the review emphasized the ability of AI to reduce diagnostic variability, improve early prediction of therapeutic response, and streamline clinical workflows. These advancements support a shift toward personalized treatment strategies and more efficient care delivery. Additionally, we outlined the expanding role of AI in clinical trials in which it supports patient stratification, endpoint prediction, and automated data integration.
Core Tip: This review focused on the integration of artificial intelligence (AI) in inflammatory bowel disease management, highlighting its applications in diagnostics, surveillance, treatment management, and clinical trial optimization. AI enables more accurate, objective, and timely evaluations of endoscopic, histological, and clinical data. By synthesizing recent advances the article emphasized the potential of AI to enhance personalized medicine and support real-time decision-making. Despite promising developments challenges remain regarding standardization, validation, and ethical concerns. This comprehensive overview outlined future directions to ensure the safe and effective implementation of AI in routine inflammatory bowel disease care.
