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Articles Published Processes
10/28/2020 4:29:58 AM | Browse: 652 | Download: 1037
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Received |
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2020-10-10 23:35 |
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Peer-Review Started |
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2020-10-10 23:35 |
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To Make the First Decision |
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Return for Revision |
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2020-10-22 03:45 |
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Revised |
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2020-10-26 01:26 |
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Second Decision |
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2020-10-26 12:25 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2020-10-26 21:16 |
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Articles in Press |
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2020-10-26 21:16 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2020-10-28 00:24 |
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Publish the Manuscript Online |
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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
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| 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
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Karen Chang, Christian S Jackson and Kenneth J Vega |
| ORCID |
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| Funding Agency and Grant Number |
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| 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 |
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