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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Nov 27, 2025; 17(11): 109991
Published online Nov 27, 2025. doi: 10.4240/wjgs.v17.i11.109991
Published online Nov 27, 2025. doi: 10.4240/wjgs.v17.i11.109991
Diagnostic value of real-time computer-aided detection for precancerous lesion during esophagogastroduodenoscopy: A meta-analysis
Zong-Yang Li, Ya-Hui Liu, Hong-Qiao Cai, Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun 130021, Jilin Province, China
Author contributions: Cai HQ designed the overall concept and outline of the manuscript; Liu YH contributed to the discussion and design of the manuscript; Li ZY contributed to the writing, and editing the manuscript, illustrations, and review of literature.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
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: Hong-Qiao Cai, MD, PhD, Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, The First Hospital of Jilin University, No. 1 Xinmin Street, Changchun 130021, Jilin Province, China. hongqiaocai@jlu.edu.cn
Received: May 28, 2025
Revised: August 16, 2025
Accepted: September 15, 2025
Published online: November 27, 2025
Processing time: 182 Days and 2.7 Hours
Revised: August 16, 2025
Accepted: September 15, 2025
Published online: November 27, 2025
Processing time: 182 Days and 2.7 Hours
Core Tip
Core Tip: This meta-analysis indicates that the artificial intelligence-enabled real-time computer-aided detection system (AI-CAD) system is superior to endoscopists in detecting precancerous lesions of the upper gastrointestinal (UGI) tract. Its sensitivity, specificity, and diagnostic accuracy are higher, which is helpful in improving lesion recognition ability and may reduce the rate of missed diagnoses. These findings support the clinical potential of integrating AI-CAD into routine endoscopy practice to enhance the early detection and prevention of UGI cancers.