Ren SQ, Chen JM, Cai C. Translational artificial intelligence in gastrointestinal and hepatic disorders: Advancing intelligent clinical decision-making for diagnosis, treatment, and prognosis. World J Gastroenterol 2025; 31(36): 110742 [DOI: 10.3748/wjg.v31.i36.110742]
Corresponding Author of This Article
Chuang Cai, PhD, Assistant Professor, Cancer Research Institute of Zhongshan City, Zhongshan City People's Hospital, No. 2 Sunwen East Road, Zhongshan 528445, Guangdong Province, China. caich6@foxmail.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. Sep 28, 2025; 31(36): 110742 Published online Sep 28, 2025. doi: 10.3748/wjg.v31.i36.110742
Translational artificial intelligence in gastrointestinal and hepatic disorders: Advancing intelligent clinical decision-making for diagnosis, treatment, and prognosis
Shu-Qi Ren, Jin-Man Chen, Chuang Cai
Shu-Qi Ren, Department of Laboratory Medicine, Zhongshan City Hospital of Integration of TCM & Western Medicine, Zhongshan 528467, Guangdong Province, China
Jin-Man Chen, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, Guangdong Province, China
Chuang Cai, Cancer Research Institute of Zhongshan City, Zhongshan City People's Hospital, Zhongshan 528445, Guangdong Province, China
Author contributions: Ren SQ, Chen JM, and Cai C made substantial contributions to this manuscript; Ren SQ conceived the review and drafted the initial manuscript; Ren SQ and Chen JM were responsible for literature collation; Ren SQ and Cai C edited and finalized the manuscript for submission; All authors reviewed and approved the submitted manuscript.
Conflict-of-interest statement: All the authors report no relevant 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: Chuang Cai, PhD, Assistant Professor, Cancer Research Institute of Zhongshan City, Zhongshan City People's Hospital, No. 2 Sunwen East Road, Zhongshan 528445, Guangdong Province, China. caich6@foxmail.com
Received: June 16, 2025 Revised: July 4, 2025 Accepted: August 22, 2025 Published online: September 28, 2025 Processing time: 97 Days and 19.3 Hours
Abstract
Gastrointestinal and hepatic disorders exhibit significant heterogeneity, characterized by complex and diverse clinical phenotypes. Most lesions present without typical symptoms in their early stages, which poses substantial challenges for early clinical identification and intervention. As an interdisciplinary field at the forefront of technology, artificial intelligence (AI) integrates theoretical innovation, algorithm development, and engineering applications, triggering paradigm shifts within the medical field. Current research trends indicate that AI technology is progressively permeating the entire diagnostic and therapeutic process for gastrointestinal and hepatic disorders, facilitating intelligent transformations in precise lesion detection, optimization of treatment decisions, and prognosis evaluation through the integration of different modal data, construction of intelligent algorithms, and establishment of clinical verification systems. This article systematically reviews the latest advancements in AI technology concerning the diagnosis and treatment of gastrointestinal diseases (such as inflammatory bowel disease and digestive system tumors) and hepatic diseases (including hepato-cirrhosis and liver cancer), emphasizing its application value and transformative potential in critical areas such as imaging omics analysis, endoscopic intelligent identification, and personalized treatment prediction.
Core Tip: Artificial intelligence (AI) demonstrates transformative potential across gastrointestinal and hepatic disorders. It enhances early detection of subtle lesions (e.g., Barrett's esophagus) by analyzing diverse clinical data, optimizes treatment decisions (e.g., therapy response in liver cancer) via integrated clinical data assessment (including multimodal integration where applicable), and refines prognostic prediction (e.g., recurrence risk in liver cancer). This translational AI enables intelligent clinical decision-making for diagnosis, personalized treatment, and prognosis assessment throughout the patient journey.
