Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models
Our findings suggest that, while PD is generally associated with a larger DAT deficit in specific brain structures of the neostriatum, it exhibits intrinsic heterogeneity across individuals, which may stem from genetic factors. Such heterogeneity can be characterized by ML models and optimally mapped into network states, providing new insights to consider when developing personalized drugs.
Authors
- Peter Shaw (ORCID: https://orcid.org/0000-0002-3187-8938)
- Yifei Han (ORCID: https://orcid.org/0000-0002-8410-0660)
- Benedictor Alexander Nguchu (ORCID: https://orcid.org/0000-0003-4146-1877)
- Yanming Wang (ORCID: https://orcid.org/0000-0003-4615-493X)
Institutions
- University of Science and Technology of China (CN)
- Wenzhou Medical University (CN)
- Affiliated Eye Hospital of Wenzhou Medical College (CN)
- Zhejiang Lab (CN)
Publication Details
- Journal
- Frontiers in Psychiatry
- Published
- 2025-02-13
- DOI
- https://doi.org/10.3389/fpsyt.2025.1453852
- Citations
- 5
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 6.95