Machine Learning Analysis of MicroRNA Expression Data Reveals Novel Diagnostic Biomarker for Ischemic Stroke.

Journal: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Published Date:

Abstract

OBJECTIVES: Ischemic stroke (IS) is one of the leading causes of morbidity and mortality worldwide. Circulating microRNAs have a potential as minimally invasive biomarkers for disease prediction, diagnosis, and prognosis. In this study, we sought to use different machine learning algorithms to identify an optimal model of microRNA by integrating the expression data of pre-selected microRNAs for discriminating patients with IS from controls.

Authors

  • Xinyi Zhao
  • Xingmei Chen
    The First Affiliated Hospital of Guangxi University of Chinese Medicine. Electronic address: 1046214726@qq.com.
  • Xulong Wu
    School of Public Health of Guangxi Medical University, Nanning, Guangxi, China.
  • Lulu Zhu
    School of Public Health of Guangxi Medical University, Nanning, Guangxi, China.
  • Jianxiong Long
    School of Public Health of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: longjx12345@163.com.
  • Li Su
    China-UK Centre for Cognition and Ageing Research, Faculty of Psychology, Southwest University, Chongqing, China.
  • Lian Gu
    The First Affiliated Hospital of Guangxi University of Chinese Medicine. Electronic address: gulian7062@163.com.