Enhancing Dementia Classification for Diverse Demographic Groups: Using Vision Transformer-Based Continuous Scoring of Clock Drawing Tests
This study demonstrates the potential of continuous CDT generated by DLNN to enhance dementia classification. By identifying demographic-specific thresholds, it offers a more inclusive and adaptive approach, which could lead to improved guidelines for using CDT in dementia screening.
Authors
- Roberto Melipillán (ORCID: https://orcid.org/0000-0003-3360-433X)
- Richard Gonzalez (ORCID: https://orcid.org/0000-0001-6334-0430)
- Laura B. Zahodne (ORCID: https://orcid.org/0000-0002-5763-4501)
- Vicki A. Freedman (ORCID: https://orcid.org/0000-0002-4604-4207)
- Yi Lu Murphey (ORCID: https://orcid.org/0000-0002-0501-8002)
- Mengyao Hu (ORCID: https://orcid.org/0000-0002-9044-9009)
- Tian Qin (ORCID: https://orcid.org/0000-0002-3466-6041)
Institutions
- University of Michigan (US)
- University of Michigan–Dearborn (US)
- The University of Texas Health Science Center (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- The Journals of Gerontology Series B
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1093/geronb/gbaf065
- Citations
- 2
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 2.94