Analysis of Two Neuroanatomical Subtypes of Parkinson's Disease and Their Motor Progression Based on Semi-Supervised Machine Learning.

Journal: CNS neuroscience & therapeutics
PMID: 39953811

Abstract

BACKGROUND: The high heterogeneity of Parkinson's disease (PD) hinders personalized interventions. Brain structure reflects damage and neuroplasticity and is one of the biological bases of symptomatology. Subtyping PD in the framework of brain structure helps in the prediction of disease trajectories and optimizes treatment strategies.

Authors

  • Hao Zhou
    State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China.
  • Yuqing Wu
    BGI-Shenzhen, Shenzhen, Guangdong, 518083, China.
  • Shuoying Chen
    Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
  • Yi Xing
    Bioinformatics Interdepartmental Graduate Program, University of California, Los Angeles, Los Angeles, CA, USA. XINGYI@email.chop.edu.
  • Jingru Ren
    Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
  • Weiguo Liu
    Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.

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