Scientometrics
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
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 by the 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
Processing time: 95 Days and 4.5 Hours
Abstract
BACKGROUND

Recently, artificial intelligence (AI) has been widely used in gastrointestinal endoscopy examinations.

AIM

To comprehensively evaluate the application of AI-assisted endoscopy in detecting different digestive diseases using bibliometric analysis.

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”. The following information was recorded from the included publications: Title, author, institution, country, endoscopy type, disease type, performance of AI, publication, citation, journal and H-index.

RESULTS

A total of 446 studies were included. The number of articles reached its peak in 2021, and the annual citation numbers increased after 2006. China, the United States and Japan were dominant countries in this field, accounting for 28.7%, 16.8%, and 15.7% of publications, respectively. The Tada Tomohiro Institute of Gastroenterology and Proctology was the most influential institution. “Cancer” and “polyps” were the hotspots in this field. Colorectal polyps were the most concerning and researched disease, followed by gastric cancer and gastrointestinal bleeding. Conventional endoscopy was the most common type of examination. The accuracy of AI in detecting Barrett’s esophagus, colorectal polyps and gastric cancer from 2018 to 2022 is 87.6%, 93.7% and 88.3%, respectively. The detection rates of adenoma and gastrointestinal bleeding from 2018 to 2022 are 31.3% and 96.2%, respectively.

CONCLUSION

AI could improve the detection rate of digestive tract diseases and a convolutional neural network-based diagnosis program for endoscopic images shows promising results.

Keywords: Bibliometric analysis; Artificial intelligence; Endoscopy; Publications; Research trends

Core Tip: Gastrointestinal tumors diagnosed at an early stage had a better prognosis than those diagnosed at a late stage, and performing endoscopy is the most effective approach to detect gastrointestinal tumors. In recent years, artificial intelligence (AI) has been widely used in gastrointestinal endoscopy examinations and it represents a fundamental breakthrough in the field of diagnostic endoscopy by assisting endoscopists with the detection of gastrointestinal tumors. This study aimed to provide a comprehensive analysis of AI applied in diagnostic endoscopy. A basic literature analysis was performed, as well as a subgroup analysis of AI-assisted digestive endoscopy in diagnosing various diseases.