Artificial intelligence in digestive diseases: Current evidence and clinical perspectives

doi:10.35712/aig.125889

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Artificial Intelligence in Gastroenterology

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2644-3236

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

Artif Intell Gastroenterol. Nov 8, 2026; 7(3): 125889
Published online Nov 8, 2026. doi: 10.35712/aig.125889

Artificial intelligence in digestive diseases: Current evidence and clinical perspectives

Mehmet Ali Kosekli, Gulali Aktas

Mehmet Ali Kosekli, Department of Internal Medicine, Division of Gastroenterology, Bolu Abant Izzet Baysal University Hospital, Bolu 14280, Türkiye

Gulali Aktas, Department of Internal Medicine, Bolu Abant Izzet Baysal University Hospital, Bolu 14280, Türkiye

Author contributions: Kosekli MA and Aktas G conceptualized the manuscript and contributed to writing, review, and editing; Aktas G performed the literature search; and Kosekli MA handled visualization.

AI contribution statement: AI was not used.

Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.

Corresponding author: Mehmet Ali Kosekli, MD, Associate Professor, Department of Internal Medicine, Division of Gastroenterology, Bolu Abant Izzet Baysal University Hospital, Golkoy, Bolu 14280, Türkiye. kosekli@gmail.com

Received: July 20, 2026
Revised: August 11, 2026
Accepted: August 31, 2026
Published online: November 8, 2026
Processing time: 107 Days and 9.1 Hours

Core Tip

Core Tip: Artificial intelligence is widely used in gastroenterology. Artificial intelligence-based models have shown promise in non-invasive fibrosis assessment, early detection of hepatocellular carcinoma, prediction of disease severity in pancreatitis, and polyp detection during endoscopy. Yet, these advances have not addressed issues of data quality, algorithm generalizability, interpretability, and clinical integration. In this paper, recent literature concerning the use of artificial intelligence in gastrointestinal endoscopy, gastrointestinal oncology, liver and pancreatic diseases, inflammatory bowel disease, motility disorders, and microbiota was reviewed.