A machine learning approach for a multidimensional analysis of functional phenotype allows for a better measurement of dementia and its severity
Our results show that the Ch-MFA achieves better results than a unidimensional assessment. Interestingly, functional dimensions that distinguish types of dementia differed from those that predict their severity. Our results suggest that a multidimensional phenotype may better reflect the specificity of dementia subtypes.
Authors
- C. Gascón Muñoz
- G. Farías
- Patricia Lillo (ORCID: https://orcid.org/0000-0001-7398-7203)
- Diego Bustamante‐Paytan (ORCID: https://orcid.org/0000-0002-1073-1961)
- Cecilia González Campo
- Belén Custodio (ORCID: https://orcid.org/0009-0007-1445-7211)
- Andrea Z. Slachevsky
- Carmen Domı́nguez
- Mauricio Cerda
- Álvaro Gallardo
- Nilton Custodio
- Rosa Montesinos
Institutions
- Universidad del Desarrollo (CL)
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- University of San Andrés (AR)
- Hospital del Salvador (CL)
- Instituto de Neurología Cognitiva (AR)
- Hospital Clínico de la Universidad de Chile (CL)
- Institute of Peruvian Studies (PE)
- Instituto de Neurociencia Biomédica (CL)
- Center for Climate and Resilience Research (CL)
- University of Chile (CL)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70857_107014
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00