Predicting Future Clinical Decline with Deep Learning, Neuroimaging, and Demographic Data
Deep learning shows promise for enhancing prognostic models; future work will include additional deep learning methods, more diverse neuroimaging data (amyloid and tau PET and diffusion MRI), and alternative data fusion methods to integrate tabular and neuroimaging data.
Authors
- Sophia I. Thomopoulos (ORCID: https://orcid.org/0000-0002-0046-4070)
- Tamoghna Chattopadhyay (ORCID: https://orcid.org/0000-0002-3146-6845)
- Nikhil J. Dhinagar (ORCID: https://orcid.org/0000-0003-2424-4854)
- Christopher J Patterson
- Emma J Gleave
- Paul M. Thompson
Institutions
- University of Southern California (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_103816
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00