Cross-modal fusion of brain imaging and clinical data for Parkinson’s disease progression prediction
The results indicate that CMFP is effective, contributing to overcoming the limitations of low predictive performance in single-modal data and enhancing the accuracy of the PD progression predictions.
Authors
- Xinhua Wei (ORCID: https://orcid.org/0000-0002-6801-4826)
- Hua Xiong (ORCID: https://orcid.org/0000-0002-2198-0162)
- Jinyu Wen (ORCID: https://orcid.org/0000-0001-9312-8289)
- Amei Chen (ORCID: https://orcid.org/0000-0002-2074-6470)
- Meie Fang (ORCID: https://orcid.org/0000-0003-4292-8889)
- Jingxin Liu (ORCID: https://orcid.org/0000-0001-6882-2228)
Institutions
- Chongqing University of Science and Technology (CN)
- Guangzhou University (CN)
- Second Affiliated Hospital of Guangzhou Medical University (CN)
- First People's Hospital of Chongqing (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-11-20
- DOI
- https://doi.org/10.1371/journal.pone.0333822
- Citations
- 1
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.39