Deep multimodal learning for domain-level cognitive decline prediction in Alzheimer's disease
This study demonstrates that AI techniques can capture patterns of cognitive decline by exploiting multimodal neuroimaging data. These findings contribute to the development of more precise phenotyping approaches for neurodegenerative patterns in AD.
Authors
- Jordi A. Matías‐Guiu (ORCID: https://orcid.org/0000-0001-5520-2708)
- José L. Ayala (ORCID: https://orcid.org/0000-0001-7236-5330)
- Fernando García‐Gutiérrez (ORCID: https://orcid.org/0000-0002-1750-8607)
Institutions
- Universidad Complutense de Madrid (ES)
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (ES)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-12-17
- DOI
- https://doi.org/10.3389/frai.2025.1731062
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Defense
- Alzheimer's Association
- Bristol-Myers Squibb
- Eli Lilly and Company
- Pfizer
- Biogen
- Meso Scale Diagnostics
- Alzheimer's Disease Neuroimaging Initiative
- BioClinica
- Novartis Pharmaceuticals Corporation
- Eisai
- Servier
- H. Lundbeck A/S
- IXICO
- National Institutes of Health
- Genentech
- Instituto de Salud Carlos III
- European Regional Development Fund