Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD)-Reference-Cited by-同舟云学术

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Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD)

Published:2024-05-03 Issue:6 Volume:23 Page:2253-2264
ISSN:1535-3893
Container-title:Journal of Proteome Research
language:en
Short-container-title:J. Proteome Res.

Author:

Li Xiaocheng¹,Xiao Yaqing¹,Chen Xinhuan²,Zhu Yayun¹,Du Haoqi¹³^ORCID,Shu Jian¹³^ORCID,Yu Hanjie¹,Ren Xiameng¹,Zhang Fan¹,Dang Jing¹,Zhang Chen¹,Su Shi²,Li Zheng¹^ORCID

Affiliation:

1. Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi’an 710069, China

2. Department of Health Science Center, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China

3. School of Medicine, Faculty of Life Sciences and Medicine, Northwest University, Xi’an 710069, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.4c00204

Reference53 articles.

1. Non-alcoholic fatty liver disease and risk of fatal and non-fatal cardiovascular events: an updated systematic review and meta-analysis

2. NAFLD and liver transplantation: Current burden and expected challenges

3. Natural history of NASH

4. Differential Clinical Characteristics and Mortality Outcomes in Persons With NAFLD and/or MAFLD

5. Incidence of Complications from Percutaneous Biopsy in Chronic Liver Disease: A Systematic Review and Meta-Analysis

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