Identification of Depression Subtypes in Parkinson's Disease Patients via Structural <scp>MRI</scp> Whole‐Brain Radiomics: An Unsupervised Machine Learning Study
By identifying MRI structural radiomics and clinical features as potential biomarkers, the radiomic approach and UCA provide new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.
Authors
- Yuguo Wei
- Qiaowei Song (ORCID: https://orcid.org/0000-0003-2549-3991)
- Jiaxuan Peng (ORCID: https://orcid.org/0000-0002-1455-1706)
- Zihan Zhang (ORCID: https://orcid.org/0000-0003-0957-9701)
- Zhenyu Shu (ORCID: https://orcid.org/0000-0002-7529-2357)
- Yuyun Xu (ORCID: https://orcid.org/0000-0002-9063-8504)
Institutions
- Zhejiang Provincial People's Hospital (CN)
- Hangzhou Medical College (CN)
- Jinzhou Medical University (CN)
Publication Details
- Journal
- CNS Neuroscience & Therapeutics
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1111/cns.70182
- Citations
- 2
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- National Natural Science Foundation of China
- Department of Health of Zhejiang Province
- Natural Science Foundation of Zhejiang Province