Enhancing early Alzheimer's disease classification accuracy through the fusion of sMRI and rsMEG data: a deep learning approach
These results highlight the value of integrating resting-state rsMEG and sMRI data in the early diagnosis of Alzheimer's disease, demonstrating significant potential in the field of neuroscience diagnostics.
Authors
- Xiaolin Ning (ORCID: https://orcid.org/0000-0003-3563-3601)
- Yang Gao (ORCID: https://orcid.org/0000-0001-9328-1611)
- Yuchen Liu (ORCID: https://orcid.org/0000-0001-7505-9718)
- Defeng Wang (ORCID: https://orcid.org/0000-0002-9530-4167)
- Ling Wang (ORCID: https://orcid.org/0000-0002-5176-7469)
Institutions
- Hefei University (CN)
- Beihang University (CN)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2024-11-20
- DOI
- https://doi.org/10.3389/fnins.2024.1480871
- Citations
- 14
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 4.80
Funders
- National Natural Science Foundation of China
- Dementias Platform UK
- Medical Research Council