Gong EJ, Woo J, Lee JJ, Bang CS. Role of artificial intelligence in gastric diseases. World J Gastroenterol 2025; 31(37): 111327 [DOI: 10.3748/wjg.v31.i37.111327]
Corresponding Author of This Article
Chang Seok Bang, MD, PhD, Professor, Department of Internal Medicine, Hallym University College of Medicine, Sakju-ro 77, Chuncheon 24253, Gangwon-do, South Korea. csbang@hallym.ac.kr
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
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 7, 2025; 31(37): 111327 Published online Oct 7, 2025. doi: 10.3748/wjg.v31.i37.111327
Role of artificial intelligence in gastric diseases
Eun Jeong Gong, Jieun Woo, Jae Jun Lee, Chang Seok Bang
Eun Jeong Gong, Chang Seok Bang, Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Gangwon-do, South Korea
Jieun Woo, Jae Jun Lee, Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24253, Gangwon-do, South Korea
Author contributions: Gong EJ, Lee JJ, and Bang CS contributed to conceptualization; Gong EJ, Woo J, and Bang CS contributed to methodology; Gong EJ wrote the original draft; Bang CS reviewed and edited the draft; Bang CS contributed to supervision; all authors contributed to investigation and agreed to the published version of the manuscript.
Supported by Hallym University Medical Center Research Fund.
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: Chang Seok Bang, MD, PhD, Professor, Department of Internal Medicine, Hallym University College of Medicine, Sakju-ro 77, Chuncheon 24253, Gangwon-do, South Korea. csbang@hallym.ac.kr
Received: June 30, 2025 Revised: July 29, 2025 Accepted: August 29, 2025 Published online: October 7, 2025 Processing time: 89 Days and 21 Hours
Core Tip
Core Tip: This minireview demonstrates that artificial intelligence (AI) in gastric disease diagnosis has reached clinical maturity, with systems achieving expert-level performance in cancer detection, precancerous lesion identification, and clinical outcome prediction. The key insight is that AI effectiveness is inversely correlated with user expertise, providing the greatest benefit to practitioners with moderate expertise. The emergence of general-purpose large language models (LLMs) represents a paradigm shift from developing custom AI models that require years of specialized training to leveraging pre-trained systems that clinicians can adapt within weeks without coding expertise. This democratization of AI technology through LLMs enables all medical professionals, regardless of their technical background, to access sophisticated AI capabilities, fundamentally changing how we integrate AI into practice.
