Meta-Analysis
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Nov 15, 2023; 15(11): 1998-2016
Published online Nov 15, 2023. doi: 10.4251/wjgo.v15.i11.1998
Application of convolutional neural network-based endoscopic imaging in esophageal cancer or high-grade dysplasia: A systematic review and meta-analysis
Jun-Qi Zhang, Jun-Jie Mi, Rong Wang
Jun-Qi Zhang, The Fifth Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
Jun-Jie Mi, Department of Gastroenterology, Shanxi Provincial People’s Hospital, Taiyuan 030012, Shanxi Province, China
Rong Wang, Department of Gastroenterology, The Fifth Hospital of Shanxi Medical University (Shanxi Provincial People’s Hospital), Taiyuan 030012, Shanxi Province, China
Author contributions: Zhang JQ conceived, designed the experiments and wrote a draft manuscript; Wang R analyzed, interpreted the results of the experiments and revised the manuscript; Mi JJ collected the clinical data and performed the experiments; and all authors read and approved the final manuscript.
Supported by the Special Program for Science and Technology Cooperation and Exchange of Shanxi, No. 202104041101034.
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: Rong Wang, MM, Chief Physician, Professor, Department of Gastroenterology, The Fifth Hospital of Shanxi Medical University (Shanxi Provincial People’s Hospital), No. 29 Shuangta West Street, Taiyuan 030012, Shanxi Province, China. wangxiongzai@126.com
Received: August 1, 2023
Peer-review started: August 1, 2023
First decision: August 22, 2023
Revised: September 5, 2023
Accepted: October 11, 2023
Article in press: October 11, 2023
Published online: November 15, 2023
Processing time: 105 Days and 21.8 Hours
Core Tip

Core Tip: This systematic review provides a meta-analysis of 28 studies evaluating the accuracy of convolutional neural network (CNN) models for diagnosing esophageal cancer and high-grade dysplasia, and for predicting the invasion depth of esophageal cancer. It also establishes a theoretical foundation for the clinical application of CNN models. Based on this meta-analysis, CNN-based image analysis may have great potential for diagnosing and estimating the prognosis of esophageal cancer, though further study is needed.