Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.

Journal: BMC gastroenterology
PMID: 39915740

Abstract

BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). The rapid development of metabolomic technologies has enabled the capture of metabolic changes related to the progression of cirrhosis.

Authors

  • Jingru Song
    Department of Gastroenterology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, Zhejiang, China.
  • Ziwei Gao
    Hangzhou School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310007, Zhejiang, China.
  • Liqun Lai
    Department of Gastroenterology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, Zhejiang, China.
  • Jie Zhang
    College of Physical Education and Health, Linyi University, Linyi, Shandong, China.
  • Binbin Liu
    Department of Business Administration, Suqian University, Suqian 223800, China.
  • Yi Sang
    Department of Gastroenterology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, Zhejiang, China.
  • Siqi Chen
    College of Animal Science and Technology, Jilin Agricultural University, Changchun, China.
  • Jiachen Qi
    Hangzhou School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310007, Zhejiang, China.
  • Yujun Zhang
    Institute of Computing Technology, Chinese Academy, China.
  • Huang Kai
    Department of cardiovascular surgery, Sun Yat-sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. huangk37@mail.sysu.edu.cn.
  • Wei Ye
    AliveX Biotech, Shanghai, China.

Keywords

External Resources

Popular Topics
Recent Journals