Investigating heterogeneity of cognitive and functional decline using Subtype and Stage Inference machine learning
We identified distinct subtypes from both participant and study partner CFI reports. Post hoc analysis indicated consistency within subtypes identified from the two sources of information. Subjective reports on cognitive decline could serve as a valuable tool for classifying participants into different risk groups.
Authors
- Ali Ezzati (ORCID: https://orcid.org/0000-0003-1307-4589)
- Ellen Grober (ORCID: https://orcid.org/0000-0001-7998-5778)
- İdris Demirsoy (ORCID: https://orcid.org/0000-0002-3321-4748)
- Bhargav Teja Nallapu (ORCID: https://orcid.org/0000-0001-6368-8509)
- Kellen K. Petersen (ORCID: https://orcid.org/0000-0003-3195-3456)
- Laura A. Rabin
- Elham Ghanbarian
- Richard Lipton
Institutions
- The Graduate Center, CUNY (US)
- Albert Einstein College of Medicine (US)
- City University of New York (US)
- University of California, Irvine (US)
- Brooklyn College (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/alz.091898
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00