Publication Name	Artificial Intelligence in Gastrointestinal Endoscopy
Manuscript ID	70270
Country	China

Received	2021-07-28 08:31
Peer-Review Started	2021-07-28 08:34
To Make the First Decision
Return for Revision	2021-09-12 06:00
Revised	2021-09-23 11:03
Second Decision	2021-10-26 07:59
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2021-10-27 03:07
Articles in Press	2021-10-27 03:07
Publication Fee Transferred
Edit the Manuscript by Language Editor	2021-10-25 03:28
Typeset the Manuscript	2021-10-27 05:58
Publish the Manuscript Online	2021-10-27 08:45

ISSN	2689-7164 (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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Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Artificial intelligence and early esophageal cancer
Manuscript Source	Invited Manuscript
All Author List	Ning Li and Shi-Zhu Jin
ORCID	Author(s) ORCID Number Ning Li http://orcid.org/0000-0002-0913-0624 Shi-Zhu Jin http://orcid.org/0000-0003-3613-0926
Funding Agency and Grant Number	Funding Agency Grant Number Heilongjiang Province Education Science "13th Five-Year Plan" 2020 Key Project GJB1320190
Corresponding Author	Shi-Zhu Jin, MD, Chief Physician, Professor, Department of Gastroenterology and Hepatology, The Second Affiliated Hospital of Harbin Medical University, No. 246 Xuefu Road, Nangang District, Harbin 150086, Heilongjiang Province, China. drshizhujin@hrbmu.edu.cn
Key Words	Artificial intelligence; Computer-aided diagnosis; Deep learning; Convolutional neural network; Barrett’s esophagus; Early esophageal cancer
Core Tip	The early diagnosis and early treatment of esophageal cancer (EC) have always been a hot spot in clinical medicine research and are of great importance to the prognosis of patients. With continuous improvements in computer technology and the arrival of the era of big data, the artificial intelligence (AI)-assisted endoscopic diagnosis of EC has also flourished. This review mainly introduces the research progress of AI-assisted endoscopy in the diagnosis of Barrett’s esophagus and early EC.
Publish Date	2021-10-27 08:45
Citation	Li N, Jin SZ. Artificial intelligence and early esophageal cancer. Artif Intell Gastrointest Endosc 2021; 2(5): 198-210
URL	https://www.wjgnet.com/2689-7164/full/v2/i5/198.htm
DOI	https://dx.doi.org/10.37126/aige.v2.i5.198

Full Article (PDF)	AIGE-2-198.pdf
Full Article (Word)	AIGE-2-198.docx
Manuscript File	70270_Auto_edited-MLWangTQ.docx
Answering Reviewers	70270-Answering reviewers.pdf
Audio Core Tip	70270-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	70270-Conflict-of-interest statement.pdf
Copyright License Agreement	70270-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	70270-Grant application form(s).pdf
Non-Native Speakers of English Editing Certificate	70270-Language certificate.pdf
Peer-review Report	70270-Peer-review(s).pdf
Scientific Misconduct Check	70270-Bing-Liu M-2.png
Scientific Editor Work List	70270-Scientific editor work list.pdf
CrossCheck Report	70270-CrossCheck report.pdf