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10/28/2020 4:29:58 AM | Browse: 539 | Download: 789
Publication Name Artificial Intelligence in Gastrointestinal Endoscopy
Manuscript ID 59952
Country/Territory United States
2020-10-10 23:35
Peer-Review Started
2020-10-10 23:35
To Make the First Decision
Return for Revision
2020-10-22 03:45
2020-10-26 01:26
Second Decision
2020-10-26 12:25
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-10-26 21:16
Articles in Press
2020-10-26 21:16
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2020-10-28 00:24
Publish the Manuscript Online
2020-10-28 04:29
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) 2020. 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 Editorial
Article Title Artificial intelligence in Barrett’s esophagus: A renaissance but not a reformation
Manuscript Source Invited Manuscript
All Author List Karen Chang, Christian S Jackson and Kenneth J Vega
Author(s) ORCID Number
Karen Chang http://orcid.org/0000-0002-1523-1587
Christian S Jackson http://orcid.org/0000-0003-4229-4206
Kenneth J Vega http://orcid.org/0000-0002-2432-6123
Funding Agency and Grant Number
Corresponding Author Kenneth J Vega, MD, Professor, Division of Gastroenterology and Hepatology, Department of Medicine, Augusta University-Medical College of Georgia, 1120 15th Street, AD 2226, Augusta, GA 30912, United States. kvega@augusta.edu
Key Words Barrett's esophagus; Artificial intelligence; Machine learning; Cognitive neural networks; Computer aided diagnosis; Endoscopy
Core Tip Screening and surveillance in patients with Barrett’s esophagus (BE) remain problematic in regards to accuracy and adherence. This occurs in spite of recommendations and advances in endoscopic imaging. Artificial intelligence (AI) algorithms assist in endoscopic evaluation of BE by identifying potential targets for biopsy. This may occur by increasing endoscopic efficiency and diagnosing accuracy by decreasing procedure time. AI in BE has been developed by expert endoscopists and appear to perform similarly among them. At this point, the benefit of AI in BE may be for use by non-expert endoscopists and trainees to maximize BE endoscopic evaluation.
Publish Date 2020-10-28 04:29
Citation Chang K, Jackson CS, Vega KJ. Artificial intelligence in Barrett’s esophagus: A renaissance but not a reformation. Artif Intell Gastrointest Endosc 2020; 1(2): 28-32
URL https://www.wjgnet.com/2689-7164/full/v1/i2/28.htm
DOI https://dx.doi.org/10.37126/aige.v1.i2.28
Full Article (PDF) AIGE-1-28.pdf
Full Article (Word) AIGE-1-28.docx
Manuscript File 59952_Auto_Edited.docx
Answering Reviewers 59952-Answering reviewers.pdf
Audio Core Tip 59952-Audio core tip.m4a
Conflict-of-Interest Disclosure Form 59952-Conflict-of-interest statement.pdf
Copyright License Agreement 59952-Copyright license agreement.pdf
Peer-review Report 59952-Peer-review(s).pdf
Scientific Misconduct Check 59952-Scientific misconduct check.pdf
Scientific Editor Work List 59952-Scientific editor work list.pdf