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-Reference-Cited by-同舟云学术

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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

Published:2024-11 Issue:6 Volume:29 Page:101540
ISSN:1665-2681
Container-title:Annals of Hepatology
language:en
Short-container-title:Annals of Hepatology

Author:

Xu Yuan,Zhang Bei,Zhou Fan,Yi Ying-ping,Yang Xin-Lei,Ouyang Xiao,Hu Hui

Funder

Jiangxi Province Department of Science and Technology

Jiangsu Provincial Key Laboratory of New Environmental Protection, Jiangsu Science and Technology Department

Key Research and Development Program of Jiangxi Province

Key Science and Technology Research Project in Jiangxi Province Department of Education

Publisher

Elsevier BV

Reference51 articles.

1. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Sung;CA Cancer J Clin,2021

2. A global assessment of recent trends in gastrointestinal cancer and lifestyle-associated risk factors;Lu;Cancer Commun.,2021

3. The hepatitis B epidemic in China should receive more attention;Chen;Lancet,2018

4. Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study;Razavi-Shearer;Lancet Gastroenterol Hepatol,2018

5. Countdown to 2030: eliminating hepatitis B disease, China;Liu;Bull World Health Organ,2019

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