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Articles Published Processes
10/28/2020 4:29:58 AM | Browse: 664 | Download: 1071
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Received |
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2020-09-21 20:06 |
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Peer-Review Started |
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2020-09-21 20:06 |
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To Make the First Decision |
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Return for Revision |
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2020-09-25 01:09 |
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Revised |
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2020-10-01 02:35 |
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Second Decision |
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2020-10-12 07:03 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2020-10-13 04:15 |
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Articles in Press |
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2020-10-13 04:15 |
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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 00:02 |
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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 |
Minireviews |
| Article Title |
Understanding deep learning in capsule endoscopy: Can artificial intelligence enhance clinical practice?
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Amporn Atsawarungruangkit, Yousef Elfanagely, Akwi W Asombang, Abbas Rupawala and Harlan G Rich |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Amporn Atsawarungruangkit, MD, Academic Fellow, Division of Gastroenterology, Warren Alpert School of Medicine, Brown University, 593 Eddy Street, POB 240, Providence, RI 02903, United States. amporn_atsawarungruangkit@brown.edu |
| Key Words |
Capsule endoscopy; Deep learning; Machine learning; Wireless capsule endoscopy; Small bowel capsule; Video capsule endoscopy |
| Core Tip |
Wireless capsule endoscopy is the least invasive endoscopy technique for investigating the gastrointestinal tract. However, it takes a significant amount of time for interpreting the results. Deep learning has been increasingly applied to interpret capsule endoscopy images. We have summarized deep learning’s framework, various characteristics in published literature, and application in the clinical setting. |
| Publish Date |
2020-10-28 04:29 |
| Citation |
Atsawarungruangkit A, Elfanagely Y, Asombang AW, Rupawala A, Rich HG. Understanding deep learning in capsule endoscopy: Can artificial intelligence enhance clinical practice? Artif Intell Gastrointest Endosc 2020; 1(2): 33-43 |
| URL |
https://www.wjgnet.com/2689-7164/full/v1/i2/33.htm |
| DOI |
https://dx.doi.org/10.37126/aige.v1.i2.33 |
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