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
Abstract
Artificial intelligence (AI) is rapidly transforming the field of gastroenterology, providing new ways to diagnose, risk-stratify, and therapeutically manage a wide variety of gastrointestinal diseases. Machine learning and deep learning algorithms are among the AI-based models that have shown promise in non-invasive fibrosis assessment, early detection of hepatocellular carcinoma, prediction of disease severity in pancreatitis, and polyp detection during endoscopy. We searched major databases, including Scopus, EMBASE, PubMed/MEDLINE, and Web of Science, and analyzed current studies on AI in gastroenterology. The integration of AI with imaging modalities, electronic health records, and multi-omics data has led to greater diagnostic accuracy and individualized patient care. Yet, these advances have not addressed issues of data quality, algorithm generalizability, interpretability, and clinical integration. Future research will focus on prospective validation of AI, regulation, and implementation to maximize the clinical utility of AI in digestive diseases. AI has the potential to improve patient outcomes, enable personalized medicine, and optimize the overall efficiency of processes involved in gastroenterological care. In this paper, recent literature concerning the use of AI in gastrointestinal endoscopy and the treatment of various gastrointestinal disorders, such as liver and pancreatic diseases, inflammatory bowel disease, and malignancies, was reviewed.
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.
