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Articles Published Processes
12/27/2021 5:24:00 AM | Browse: 503 | Download: 889
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Received |
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2021-05-28 21:03 |
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Peer-Review Started |
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2021-05-28 21:06 |
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To Make the First Decision |
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Return for Revision |
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2021-07-06 01:56 |
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Revised |
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2021-07-19 21:14 |
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Second Decision |
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2021-11-12 03:21 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-11-15 03:08 |
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Articles in Press |
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2021-11-15 03:08 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2021-11-09 22:27 |
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Typeset the Manuscript |
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2021-12-13 08:57 |
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Publish the Manuscript Online |
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2021-12-27 05:24 |
| ISSN |
1948-5182 (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) 2021. 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 |
Deep learning in hepatocellular carcinoma: Current status and future perspectives
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Joseph C Ahn, Touseef Ahmad Qureshi, Amit G Singal, Debiao Li and Ju-Dong Yang |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Ju-Dong Yang, MD, MS, Assistant Professor, Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8900 Beverly Blvd, Los Angeles, CA 90048, United States. judong.yang@cshs.org |
| Key Words |
Hepatocellular carcinoma; Artificial intelligence; Deep learning |
| Core Tip |
There are emerging roles for deep learning technology in the field of hepatocellular carcinoma (HCC) including HCC risk prediction, as well as diagnosis, prognostication, and treatment planning leveraging readily available data from radiologic and histopathologic medical images. This article will provide a comprehensive review of the recently published studies that have applied deep learning for risk prediction, diagnosis, prognostication, and treatment planning for patients with HCC. |
| Publish Date |
2021-12-27 05:24 |
| Citation |
Ahn JC, Qureshi TA, Singal AG, Li D, Yang JD. Deep learning in hepatocellular carcinoma: Current status and future perspectives. World J Hepatol 2021; 13(12): 2039-2051 |
| URL |
https://www.wjgnet.com/1948-5182/full/v13/i12/2039.htm |
| DOI |
https://dx.doi.org/10.4254/wjh.v13.i12.2039 |
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