De Silva AP, Prabagar K. Artificial intelligence in gastroenterology: Enhancing clinical practice, managing challenges and exploring future directions. Artif Intell Gastroenterol 2025; 6(2): 110109 [DOI: 10.35712/aig.v6.i2.110109]
Corresponding Author of This Article
Arjuna Priyadarsin De Silva, Professor, Department of Medicine, Faculty of Medicine, University of Kelaniya, Thalagolla Road, Ragama 11010, Western, Sri Lanka. apdsilva@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/
Artificial intelligence in gastroenterology: Enhancing clinical practice, managing challenges and exploring future directions
Arjuna Priyadarsin De Silva, Krishanni Prabagar
Arjuna Priyadarsin De Silva, Krishanni Prabagar, Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama 11010, Western, Sri Lanka
Author contributions: De Silva AP conceptualized and supervised the study, provided critical revisions for important intellectual content, and guided the overall structure of the manuscript; Prabagar K conducted the literature review, performed the analysis, interpreted the data, and drafted the original manuscript; Both authors prepared the final draft and approved the submitted version.
Conflict-of-interest statement: The authors declare no conflicts of interest for this article.
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: Arjuna Priyadarsin De Silva, Professor, Department of Medicine, Faculty of Medicine, University of Kelaniya, Thalagolla Road, Ragama 11010, Western, Sri Lanka. apdsilva@yahoo.com
Received: May 29, 2025 Revised: June 16, 2025 Accepted: September 10, 2025 Published online: September 28, 2025 Processing time: 122 Days and 13.5 Hours
Abstract
Artificial intelligence (AI) is transforming gastroenterology by enhancing diagnostic accuracy, enabling personalized treatment, and improving disease management efficiency. This review explored the evolution and application of core AI technologies, including machine learning, deep learning, and neural networks, that underpin modern computational advancements in the field. These tools have demonstrated significant success in detecting premalignant and malignant lesions and in managing gastrointestinal bleeding, colorectal cancer, and Helicobacter pylori infection. AI also supports the diagnosis and treatment of liver and pancreatic diseases. Its use is expanding in functional gastrointestinal disorders such as irritable bowel syndrome with emerging applications in pediatric gastroenterology. In addition AI enables advanced risk stratification and addresses persistent challenges in conventional diagnostic and therapeutic approaches, including interobserver variability and inefficiencies in care delivery. However, integration into routine clinical practice faces several barriers, including data privacy concerns, algorithmic bias, limited model interpretability, regulatory gaps, and interoperability issues with existing healthcare infrastructure. Future directions include real-time procedural guidance, multi-omic prediction models, minimally invasive surgical automation, and drug discovery. Achieving the full potential of AI will require ethical governance, regulatory clarity, and sustained interdisciplinary collaboration.
Core Tip: Artificial intelligence (AI) is being applied across a range of gastrointestinal conditions from cancer and liver disease to functional disorders and is driving the development of new tools in digital health. It has demonstrated equal or superior efficiency compared with humans in diagnostic accuracy, treatment planning, and healthcare delivery. However, several important challenges remain, including data privacy concerns, limited transparency of algorithms, inherent biases, and difficulties integrating AI into traditional clinical workflows. Addressing these issues is essential for clinicians to fully benefit from AI and for its continued development in the field.
