Publication Name	World Journal of Hepatology
Manuscript ID	105332
Country	China

Category	Endocrinology & Metabolism
Manuscript Type	Basic Study
Article Title	Machine learning to identify potential biomarkers for sarcopenia in liver cirrhosis
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
Funding Agency and Grant Number	Funding Agency Grant Number The Medical Key Science and Technology Project of Shanxi Province No. 2020xm23
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	Cirrhosis; Sarcopenia; Untargeted metabolomics; Machine learning; Biomarkers
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.
Citation	Liang Q, Wang J, Yang Y, Zhao K, Luo R, Tian Y, Li F. Machine learning to identify potential biomarkers for sarcopenia in liver cirrhosis. World J Hepatol 2025; In press

Received	2025-01-20 11:09
Peer-Review Started	2025-01-20 11:09
To Make the First Decision
Return for Revision	2025-02-28 14:26
Revised	2025-03-30 08:43
Second Decision	2025-04-27 02:43
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-04-27 08:15
Articles in Press	2025-04-27 08:15
Publication Fee Transferred	2025-04-03 02:32
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1948-5182 (online)
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