Expanding the Use of Machine Learning ADRD Indices to Diverse Neuroimaging Samples from the CHARGE Consortium
Robust harmonization techniques and ML model training using diverse neuroimaging datasets can facilitate the expansion of ML indices to different racial and ethnic groups. Older Hispanic individuals may have a different relationship between aging-related brain atrophy patterns and cognition, which might indicate differences in underlying neuropathologies or other unidentified factors.
Authors
- Timothy J. Hohman (ORCID: https://orcid.org/0000-0002-3377-7014)
- Derek B. Archer (ORCID: https://orcid.org/0000-0001-8638-0785)
- Christos A. Davatzikos (ORCID: https://orcid.org/0000-0002-1025-8561)
- José Gutierrez (ORCID: https://orcid.org/0000-0002-2175-8078)
- Sokratis Charisis (ORCID: https://orcid.org/0000-0001-6578-393X)
- W.T. Longstreth
- Sachintha Ransara Brandigampala
- Timothy M. Hughes
- Di Wang
- Susan R. Heckbert
- Mohamad Habes
- David M Martinez
- Claudia L Satizabal
- Charles S. DeCarli
- Sudha Seshadri
- Tatjana Rundek
Institutions
- University of Miami (US)
- The University of Texas at San Antonio Health Science Center (US)
- University of Washington (US)
- Columbia University Irving Medical Center (US)
- Institute for Neurodegenerative Disorders (US)
- Institute on Aging (US)
- The University of Texas at San Antonio (US)
- Wake Forest University (US)
- University of Pennsylvania (US)
- University of California, Davis (US)
- Vanderbilt University Medical Center (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_103021
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00