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Articles Published Processes
6/26/2025 7:27:53 AM | Browse: 92 | Download: 478
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Received |
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2025-01-20 11:09 |
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Peer-Review Started |
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2025-01-20 11:09 |
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First Decision by Editorial Office Director |
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2025-02-26 01:57 |
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Return for Revision |
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2025-02-28 14:26 |
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Revised |
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2025-03-30 08:43 |
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Publication Fee Transferred |
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2025-04-03 02:32 |
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Second Decision by Editor |
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2025-04-27 02:43 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2025-04-27 08:15 |
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Articles in Press |
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2025-04-27 08:15 |
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Edit the Manuscript by Language Editor |
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2025-05-03 20:17 |
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Typeset the Manuscript |
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2025-06-16 07:40 |
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Publish the Manuscript Online |
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2025-06-26 07:27 |
| 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: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2025. 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 |
Endocrinology & Metabolism |
| Manuscript Type |
Basic Study |
| Article Title |
Machine learning to identify potential biomarkers for sarcopenia in liver cirrhosis
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Qian-Yu Liang, Jun Wang, Yun-Feng Yang, Kai Zhao, Rui-Li Luo, Ye Tian and Feng-Xia Li |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| The Medical Key Science and Technology Project of Shanxi Province |
No. 2020xm23 |
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| Corresponding Author |
Feng-Xia Li, Department of Gastroenterology, Shanxi Provincial People's Hospital, No. 29 Shuangta Temple Street, Yingze District, Taiyuan 030000, Shanxi Province, China. doclfx@126.com |
| Key Words |
Biomarkers; Machine learning; Untargeted metabolomics; Sarcopenia; Cirrhosis |
| Core Tip |
This study unveiled different plasma metabolic profiles of liver cirrhosis patients with and without sarcopenia, which may deliver valuable biomarkers for the early identification and prognosis prediction of the disease. |
| Publish Date |
2025-06-26 07:27 |
| Citation |
Liang QY, Wang J, Yang YF, Zhao K, Luo RL, Tian Y, Li FX. Machine learning to identify potential biomarkers for sarcopenia in liver cirrhosis. World J Hepatol 2025; 17(6): 105332 |
| URL |
https://www.wjgnet.com/1948-5182/full/v17/i6/105332.htm |
| DOI |
https://dx.doi.org/10.4254/wjh.v17.i6.105332 |
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