Use of machine learning method on automatic classification of motor subtype of Parkinson's disease based on multilevel indices of rs-fMRI.

Journal: Parkinsonism & related disorders
PMID: 34399160

Abstract

OBJECTIVE: This study aimed to develop an automatic classifier to distinguish different motor subtypes of Parkinson's disease (PD) based on multilevel indices of resting-state functional magnetic resonance imaging (rs-fMRI).

Authors

  • HuiZe Pang
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China. Electronic address: ophelia0702@163.com.
  • ZiYang Yu
    School of Medicine, Xiamen University, Xiamen, 361000, Fujian, PR China.
  • Hongmei Yu
    Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • JiBin Cao
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China.
  • YingMei Li
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China.
  • MiaoRan Guo
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China.
  • ChengHao Cao
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China.
  • GuoGuang Fan
    Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, PR China. Electronic address: fanguog@sina.com.

Keywords

External Resources

Popular Topics
Recent Journals