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10/27/2021 9:28:12 AM | Browse: 330 | Download: 727
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 Company 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.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
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
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