
94% of researchers rate our articles as excellent or good
Learn more about the work of our research integrity team to safeguard the quality of each article we publish.
Find out more
CORRECTION article
Front. Med. , 14 May 2021
Sec. Gastroenterology
Volume 8 - 2021 | https://doi.org/10.3389/fmed.2021.698483
This article is part of the Research Topic Recent Updates in Advanced Gastrointestinal Endoscopy View all 25 articles
This article is a correction to:
Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis
by Jiang, K., Jiang, X., Pan, J., Wen, Y., Huang, Y., Weng, S., et al. (2021). Front. Med. 8:629080. doi: 10.3389/fmed.2021.629080
The authors' names and surnames were accidentally inverted. The correct author list appears below:
Kailin Jiang1, Xiaotao Jiang1, Jinglin Pan2, Yi Wen3, Yuanchen Huang1, Senhui Weng1, Shaoyang Lan3, Kechao Nie1, Zhihua Zheng1, Shuling Ji1, Peng Liu1, Peiwu Li3* and Fengbin Liu3*
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated
Keywords: artificial intelligence, machine learning, deep learning, early gastric cancer, endoscopy
Citation: Jiang K, Jiang X, Pan J, Wen Y, Huang Y, Weng S, Lan S, Nie K, Zheng Z, Ji S, Liu P, Li P and Liu F (2021) Corrigendum: Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis. Front. Med. 8:698483. doi: 10.3389/fmed.2021.698483
Received: 21 April 2021; Accepted: 23 April 2021;
Published: 14 May 2021.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2021 Jiang, Jiang, Pan, Wen, Huang, Weng, Lan, Nie, Zheng, Ji, Liu, Li and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Peiwu Li, ZG9jdG9ybGlwd0BnenVjbS5lZHUuY24=; Fengbin Liu, bGl1ZmIxNjNAdmlwLjE2My5jb20=
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Research integrity at Frontiers
Learn more about the work of our research integrity team to safeguard the quality of each article we publish.