Machine Learning Algorithms for Predicting Fatty Liver Disease.

Journal: Annals of nutrition & metabolism
PMID: 33849025

Abstract

BACKGROUND: Fatty liver disease (FLD) has become a rampant condition. It is associated with a high rate of morbidity and mortality in a population. The condition is commonly referred as FLD. Early prediction of FLD would allow patients to take necessary preventive, diagnosis, and treatment. The main objective of this research is to develop a machine learning (ML) model to predict FLD that can help medics to classify individuals at high risk of FLD, make novel diagnosis, management, and prevention for FLD.

Authors

  • Xieyi Pei
    Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Qingqing Deng
    Department of Geriatrics, The First People's Hospital of Xiangtan City, Xiangtan, China.
  • Zhuo Liu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiang Yan
    Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Weiping Sun
    Department of Geriatrics, The First People's Hospital of Xiangtan City, Xiangtan, China.

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