Automatic Classification on Multi-Modal MRI Data for Diagnosis of the Postural Instability and Gait Difficulty Subtype of Parkinson's Disease.

Journal: Journal of Parkinson's disease
Published Date: May 11, 2016

Abstract

BACKGROUND: Patients with the postural instability and gait difficulty subtype (PIGD) of Parkinson's disease (PD) are a refractory challenge in clinical practice. Despite previous attempts that have been made at studying subtype-specific brain alterations across PD population, conclusive neuroimaging biomarkers on patients with the PIGD subtype are still lacking. Machine learning-based classifications are a promising tool for differential diagnosis that effectively integrate complex and multivariate data.

Authors

  • Quanquan Gu
    Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Huan Zhang
    Department of Plant Protection, Zhejiang University, 866 Yuhangtang Road, 5 Hangzhou 310058, China.
  • Min Xuan
    Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Wei Luo
    Centre for Pattern Recognition and Data Analytics, School of Information Technology, Deakin University, Geelong, Victoria, Australia.
  • Peiyu Huang
    Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Shunren Xia
    Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.
  • Minming Zhang
    Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China. zhangminming@zju.edu.cn.

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