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Articles Published Processes
7/9/2021 8:50:00 AM | Browse: 632 | Download: 776
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Received |
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2021-05-13 06:56 |
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Peer-Review Started |
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2021-05-13 06:58 |
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To Make the First Decision |
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Return for Revision |
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2021-06-02 13:56 |
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Revised |
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2021-06-19 15:01 |
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Second Decision |
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2021-06-30 00:36 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-06-30 00:42 |
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Articles in Press |
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2021-06-30 00:42 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2021-07-08 17:46 |
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Typeset the Manuscript |
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2021-07-09 05:24 |
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Publish the Manuscript Online |
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2021-07-09 08:50 |
ISSN |
2644-3260 (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 |
Oncology |
Manuscript Type |
Minireviews |
Article Title |
Application of radiomics in hepatocellular carcinoma: A review
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Manuscript Source |
Invited Manuscript |
All Author List |
Zhi-Cheng Jin and Bin-Yan Zhong |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Bin-Yan Zhong, MD, PhD, Doctor, Doctor, Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, 188 Shizi St, Suzhou 215006, Jiangsu Province, China. byzhongir@sina.com |
Key Words |
Hepatocellular carcinoma; Radiomics; Machine learning; Deep learning; Radiogenomics |
Core Tip |
The high molecular heterogeneity in hepatocellular carcinoma (HCC) poses huge challenges for clinical practice or trial design and has become a major barrier to improving the management of HCC. Radiomics method could quantify tumoral phenotypes and heterogeneity, which may provide benefits in clinical decision-making at a lower cost. Here, we review the workflow and application of radiomics in HCC. |
Publish Date |
2021-07-09 08:50 |
Citation |
Jin ZC, Zhong BY. Application of radiomics in hepatocellular carcinoma: A review. Artif Intell Med Imaging 2021; 2(3): 64-72 |
URL |
https://www.wjgnet.com/2644-3260/full/v2/i3/64.htm |
DOI |
https://dx.doi.org/10.35711/aimi.v2.i3.64 |
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