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Development of machine learning-based personalized predictive models for risk evaluation of hepatocellular carcinoma in hepatitis B virus-related cirrhosis patients with low levels of serum alpha-fetoprotein

Crossref DOI link: https://doi.org/10.1016/j.aohep.2024.101540

Published Print: 2024-11

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Xu, Yuan

Zhang, Bei

Zhou, Fan

Yi, Ying-ping

Yang, Xin-Lei

Ouyang, Xiao

Hu, Hui
Funding

Funding for this research was provided by:

Jiangxi Province Department of Science and Technology

Jiangsu Provincial Key Laboratory of New Environmental Protection, Jiangsu Science and Technology Department (20212BAG70012)

Key Research and Development Program of Jiangxi Province (20202BBEL53005, 20202BBGL73040)

Key Science and Technology Research Project in Jiangxi Province Department of Education (20212ABC03A37)
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Text and Data Mining valid from 2024-11-01

Text and Data Mining valid from 2024-11-01

Version of Record valid from 2024-08-09
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This article is maintained by: Elsevier

Article Title: Development of machine learning-based personalized predictive models for risk evaluation of hepatocellular carcinoma in hepatitis B virus-related cirrhosis patients with low levels of serum alpha-fetoprotein

Journal Title: Annals of Hepatology

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.aohep.2024.101540

Content Type: article

Copyright: © 2024 Fundación Clínica Médica Sur, A.C. Published by Elsevier España, S.L.U.

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