Predicting cognitive decline from neuropsychiatric symptoms and Alzheimer's disease biomarkers: A machine learning approach to a population-based data
NPS, added to ML models including demographic and AD biomarker data, improves prediction of downward trajectories in global and domain-specific cognitive scores among community-dwelling older adults, albeit effect sizes are small. These preliminary findings need to be confirmed by future cohort studies.
Authors
- Jay Shah (ORCID: https://orcid.org/0000-0002-3617-2395)
- Yiming Che (ORCID: https://orcid.org/0000-0003-0231-4524)
- Erica Forzani (ORCID: https://orcid.org/0000-0003-2407-8251)
- Ronald Carl Petersen (ORCID: https://orcid.org/0000-0002-8178-6601)
- Yonas E. Geda (ORCID: https://orcid.org/0000-0003-1187-7230)
- David S. Knopman (ORCID: https://orcid.org/0000-0002-6544-066X)
- Teresa Wu (ORCID: https://orcid.org/0000-0002-0529-7048)
- Cliff R Jack
- Janina Krell-Roesch
Institutions
- Karlsruhe Institute of Technology (DE)
- Barrow Neurological Institute (US)
- Mayo Clinic in Arizona (US)
- Advanced Imaging Research (United States) (US)
- Mayo Clinic in Florida (US)
- Arizona State University (US)
Publication Details
- Journal
- Journal of Alzheimer s Disease
- Published
- 2025-01-10
- DOI
- https://doi.org/10.1177/13872877241306654
- Citations
- 6
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 8.83
Funders
- National Institutes of Health