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Articles Published Processes
10/21/2020 3:38:05 PM | Browse: 496 | Download: 906
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Received |
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2020-07-16 12:43 |
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Peer-Review Started |
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2020-07-16 12:44 |
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To Make the First Decision |
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Return for Revision |
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2020-08-08 17:38 |
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Revised |
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2020-08-22 09:57 |
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Second Decision |
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2020-09-03 10:12 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2020-09-04 03:03 |
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Articles in Press |
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2020-09-04 03:03 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2020-09-17 04:02 |
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Typeset the Manuscript |
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2020-10-19 00:56 |
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Publish the Manuscript Online |
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2020-10-21 15:38 |
| 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 |
Minireviews |
| Article Title |
Artificial intelligence technique in detection of early esophageal cancer
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Lu-Ming Huang, Wen-Juan Yang, Zhi-Yin Huang, Cheng-Wei Tang and Jing Li |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Key Research and Development Program of Science and Technology Department of Sichuan Province |
2018GZ0088 |
| Science & Technology Bureau of Chengdu, China |
2017-CY02-00023-GX |
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| Corresponding Author |
Jing Li, MD, PhD, Associate Professor, Department of Gastroenterology, West China Hospital Sichuan University, No. 37 Guoxue Lane, Chengdu 610041, Sichuan Province, China. melody224@163.com |
| Key Words |
Artificial intelligence; Early esophageal cancer; Barrett's esophagus; Esophageal squamous cell carcinoma; Endoscopic diagnosis; Pathological diagnosis |
| Core Tip |
The requirement for more efficient methods of detection and characterization of early esophageal cancer (EC) has led to intensive research in the field of artificial intelligence (AI). Thus, application of AI technique in endoscopic detection of early EC was reviewed intensively. Furthermore, pathological and gene diagnosis for early EC as well as its risk stratification was also commented respectively. |
| Publish Date |
2020-10-21 15:38 |
| Citation |
Huang LM, Yang WJ, Huang ZY, Tang CW, Li J. Artificial intelligence technique in detection of early esophageal cancer. World J Gastroenterol 2020; 26(39): 5959-5969 |
| URL |
https://www.wjgnet.com/1007-9327/full/v26/i39/5959.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v26.i39.5959 |
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