Laboratory parameter-based machine learning model for excluding non-alcoholic fatty liver disease (NAFLD) in the general population.

Journal: Alimentary pharmacology & therapeutics
PMID: 28585725

Abstract

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 20%-40% of the general population in developed countries and is an increasingly important cause of hepatocellular carcinoma. Electronic medical records facilitate large-scale epidemiological studies, existing NAFLD scores often require clinical and anthropometric parameters that may not be captured in those databases.

Authors

  • T C-F Yip
    Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong.
  • A J Ma
    Department of Computer Science, Hong Kong Baptist University, Hong Kong.
  • V W-S Wong
    Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong.
  • Y-K Tse
    Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong.
  • H L-Y Chan
    Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong.
  • P-C Yuen
    Department of Computer Science, Hong Kong Baptist University, Hong Kong.
  • G L-H Wong
    Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong.

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