Six-gene prognostic signature for non-alcoholic fatty liver disease susceptibility using machine learning.

Journal: Medicine
Published Date:

Abstract

BACKGROUND: nonalcoholic fatty liver disease (NAFLD) is a common liver disease affecting the global population and its impact on human health will continue to increase. Genetic susceptibility is an important factor influencing its onset and progression, and there is a lack of reliable methods to predict the susceptibility of normal populations to NAFLD using appropriate genes.

Authors

  • Xiang Zhang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Chunzi Zhou
    Zhejiang Chinese Medical University, Hangzhou, China.
  • Jingwen Hu
    Department of Thoracic Surgery, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing, China.
  • Yueping Ding
    Department of Critical Care Medicine, The Second Affiliated Hospital of Zhejiang Chinese Medical University, 318 Chaowang Road, Hangzhou, 31000, Zhejiang, China. Dingyp0424@zcmu.edu.cn.
  • Shiqi Chen
    Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Xu Wang
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.
  • Lei Xu
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
  • Zhijun Gou
    Zhejiang Chinese Medical University, Hangzhou, China.
  • Shuqiao Zhang
    First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Weiqun Shi
    The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.