Du RC, Ouyang YB, Hu Y. Research trends on artificial intelligence and endoscopy in digestive diseases: A bibliometric analysis from 1990 to 2022. World J Gastroenterol 2023; 29(22): 3561-3573 [PMID: 37389238 DOI: 10.3748/wjg.v29.i22.3561]
Corresponding Author of This Article
Yi Hu, MD, Doctor, Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17 Yong Waizheng Street, Donghu District, Nanchang 330006, Jiangxi Province, China. ndyfy06202@ncu.edu.cn
Research Domain of This Article
Oncology
Article-Type of This Article
Scientometrics
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. Jun 14, 2023; 29(22): 3561-3573 Published online Jun 14, 2023. doi: 10.3748/wjg.v29.i22.3561
Research trends on artificial intelligence and endoscopy in digestive diseases: A bibliometric analysis from 1990 to 2022
Ren-Chun Du, Yao-Bin Ouyang, Yi Hu
Ren-Chun Du, Yao-Bin Ouyang, Yi Hu, Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
Yao-Bin Ouyang, Department of Oncology, Mayo Clinic, Rochester, MN 55905, United States
Yi Hu, Department of Surgery, The Chinese University of Hong Kong, Hong Kong 999077, China
Author contributions: Du RC and Ouyang YB performed the literature search and collected the data; Du RC performed the statistical analysis and wrote the manuscript; Hu Y designed the study, conceived and revised the manuscript; and all authors contributed to the article and approved the final manuscript.
Supported bythe National Natural Science Foundation of China, No. 82000531; Project for Academic and Technical Leaders of Major Disciplines in Jiangxi Province, No. 20212BCJL23065; Key Research and Development Program of Jiangxi Province, No. 20212BBG73018; and Youth Project of the Jiangxi Natural Science Foundation, No. 20202BABL216006.
Conflict-of-interest statement: The authors declare having no conflicts of interest.
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: Yi Hu, MD, Doctor, Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17 Yong Waizheng Street, Donghu District, Nanchang 330006, Jiangxi Province, China. ndyfy06202@ncu.edu.cn
Received: March 4, 2023 Peer-review started: March 4, 2023 First decision: March 28, 2023 Revised: April 3, 2023 Accepted: May 4, 2023 Article in press: May 4, 2023 Published online: June 14, 2023
ARTICLE HIGHLIGHTS
Research background
Recently, artificial intelligence (AI) has been widely used in gastrointestinal endoscopy examinations.
Research motivation
More than 100 million subjects receive gastrointestinal endoscopy examinations each year. It is of great importance to improve the quality of endoscopy examinations to discover the lesions. With the development of AI, it has been extensively used in gastrointestinal endoscopy examinations.
Research objectives
To provide a comprehensive analysis of AI applied in diagnostic endoscopy.
Research methods
Relevant publications from the Web of Science published from 1990 to 2022 were extracted using a combination of the search terms “AI” and “endoscopy”.
Research results
AI-assisted digestive endoscopy could improve the diagnosis rate of endoscopists in disease detection, and convolutional neural network-based diagnosis programs for endoscopic images showed promising results.
Research conclusions
AI could improve the detection rate of digestive tract diseases and has been applied widely in the field of endoscopy. Multicenter prospective studies with larger samples should be conducted in the future to further explore the accuracy of AI based on different methods.
Research perspectives
Gastrointestinal cancers seriously threaten the health of global populations. Gastrointestinal tumors diagnosed at an early stage had a better prognosis than those diagnosed at a late stage. AI represents a fundamental breakthrough in the field of diagnostic endoscopy by assisting endoscopists with the detection of gastrointestinal tumors and it has been extensively used in gastrointestinal endoscopy examinations.
