Comparison and development of advanced machine learning tools to predict nonalcoholic fatty liver disease: An extended study-Reference-Cited by-同舟云学术

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Comparison and development of advanced machine learning tools to predict nonalcoholic fatty liver disease: An extended study

Published:2021-10 Issue:5 Volume:20 Page:409-415
ISSN:1499-3872
Container-title:Hepatobiliary & Pancreatic Diseases International
language:en
Short-container-title:Hepatobiliary & Pancreatic Diseases International

Author:

Liu Yuan-Xing,Liu Xi,Cen Chao,Li Xin,Liu Ji-Min,Ming Zhao-Yan,Yu Song-Feng,Tang Xiao-Feng,Zhou Lin,Yu Jun,Huang Ke-Jie,Zheng Shu-Sen

Publisher

Elsevier BV

Subject

Gastroenterology,Hepatology

Reference30 articles.

1. Nonalcoholic fatty liver disease: basic pathogenetic mechanisms in the progression from NAFLD to NASH;Pierantonelli;Transplantation,2019

2. How good is controlled attenuation parameter and fatty liver index for assessing liver steatosis in general population: correlation with ultrasound;Carvalhana;Liver Int,2014

3. External validation of the fatty liver index for identifying nonalcoholic fatty liver disease in a population-based study;Koehler;Clin Gastroenterol Hepatol,2013

4. Non-invasive assessment of non-alcoholic fatty liver disease: clinical prediction rules and blood-based biomarkers;Vilar-Gomez;J Hepatol,2018

5. Development and validation of a clinical and laboratory-based nomogram to predict nonalcoholic fatty liver disease;Cen;Hepatol Int,2020

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