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Articles Published Processes
12/19/2020 11:55:31 AM | Browse: 650 | Download: 1153
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Received |
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2020-10-13 17:11 |
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Peer-Review Started |
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2020-10-13 17:12 |
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To Make the First Decision |
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Return for Revision |
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2020-11-13 17:03 |
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Revised |
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2020-11-18 18:08 |
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Second Decision |
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2020-11-25 13:39 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2020-11-29 04:06 |
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Articles in Press |
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2020-11-29 04:06 |
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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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2020-12-15 02:40 |
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Publish the Manuscript Online |
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2020-12-19 11:55 |
| 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) 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 |
Opinion Review |
| Article Title |
Artificial intelligence-aided colonoscopy: Recent developments and future perspectives
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Giulio Antonelli, Paraskevas Gkolfakis, Georgios Tziatzios, Ioannis S Papanikolaou, Konstantinos Triantafyllou and Cesare Hassan |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Paraskevas Gkolfakis, MD, Consultant Physician-Scientist, Department of Gastroenterology Hepatopancreatology and Digestive Oncology, Erasme University Hospital, Université Libre de Bruxelles, Rue de Lennik 808, Brussels 1070, Belgium. pgkolfakis@med.uoa.gr |
| Key Words |
Artificial intelligence; Colonoscopy; Polyp; Adenoma; Detection; Characterization |
| Core Tip |
Artificial intelligence systems using deep learning techniques are constantly developing in all fields of medicine including diagnostic colonoscopy. They aim to become part of daily routine and eliminate inherent examination’s shortcomings and lead to a higher level of provided health services. In this opinion review we present the existing evidence regarding the impact of artificial intelligence systems on the improvement of colonoscopy’s outcomes, namely adenoma detection rate and adenoma miss rate, focusing mainly on clinical trials and meta-analyses evaluating real-time computer aided detection and characterization. |
| Publish Date |
2020-12-19 11:55 |
| Citation |
Antonelli G, Gkolfakis P, Tziatzios G, Papanikolaou IS, Triantafyllou K, Hassan C. Artificial intelligence-aided colonoscopy: Recent developments and future perspectives. World J Gastroenterol 2020; 26(47): 7436-7443 |
| URL |
https://www.wjgnet.com/1007-9327/full/v26/i47/7436.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v26.i47.7436 |
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