Publication Name	World Journal of Gastroenterology
Manuscript ID	63075
Country	China

Received	2021-01-24 02:06
Peer-Review Started	2021-01-24 02:11
To Make the First Decision
Return for Revision	2021-03-14 06:13
Revised	2021-03-27 11:59
Second Decision	2021-04-08 12:59
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2021-04-09 18:45
Articles in Press	2021-04-09 18:45
Publication Fee Transferred
Edit the Manuscript by Language Editor	2021-04-15 19:20
Typeset the Manuscript	2021-05-19 00:59
Publish the Manuscript Online	2021-05-20 08:38

ISSN	1007-9327 (print) and 2219-2840 (online)
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: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright	© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
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Website	http://www.wjgnet.com

Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Deep learning for diagnosis of precancerous lesions in upper gastrointestinal endoscopy: A review
Manuscript Source	Invited Manuscript
All Author List	Tao Yan, Pak Kin Wong and Ye-Ying Qin
ORCID	Author(s) ORCID Number Tao Yan http://orcid.org/0000-0002-8929-015X Pak Kin Wong http://orcid.org/0000-0002-7623-6904 Ye-Ying Qin http://orcid.org/0000-0002-7779-1045
Funding Agency and Grant Number	Funding Agency Grant Number The Science and Technology Development Fund, Macau SAR 0021/2019/A
Corresponding Author	Pak Kin Wong, PhD, Professor, Department of Electromechanical Engineering, University of Macau, Avenida da Universidade, Taipa 999078, Macau, China. fstpkw@um.edu.mo
Key Words	Artificial intelligence; Deep learning; Convolutional neural network; Precancerous lesions; Endoscopy
Core Tip	Artificial intelligence (AI) techniques, especially deep learning (DL) algorithms with convolutional neural networks, have revolutionized upper gastrointestinal (GI) endoscopy. In recent years, several DL-based AI systems have emerged in the GI community for endoscopic detection of precancerous lesions. The current review provides an analysis of the DL-based diagnosis of precancerous lesions in the upper GI tract, states the current status, and identifies future challenges and recommendations.
Publish Date	2021-05-20 08:38
Citation	Yan T, Wong PK, Qin YY. Deep learning for diagnosis of precancerous lesions in upper gastrointestinal endoscopy: A review. World J Gastroenterol 2021; 27(20): 2531-2544
URL	https://www.wjgnet.com/1007-9327/full/v27/i20/2531.htm
DOI	https://dx.doi.org/10.3748/wjg.v27.i20.2531

Full Article (PDF)	WJG-27-2531.pdf
Full Article (Word)	WJG-27-2531.docx
Manuscript File	63075-Review-FilipodiaCL.docx
Answering Reviewers	63075-Answering reviewers.pdf
Audio Core Tip	63075-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	63075-Conflict-of-interest statement.pdf
Copyright License Agreement	63075-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	63075-Grant application form(s).pdf
Non-Native Speakers of English Editing Certificate	63075-Language certificate.pdf
Peer-review Report	63075-Peer-review(s).pdf
Scientific Misconduct Check	63075-Bing-Liu M-1.png
Scientific Misconduct Check	63075-Bing-Fan JR-2.png
Scientific Misconduct Check	63075-Scientific misconduct check.pdf
Scientific Editor Work List	63075-Scientific editor work list.pdf