Leveraging Routine Blood Tests, Plasma pTau‐217, and Machine Learning for Enhanced Detection and Monitoring of Preclinical Alzheimer's Disease
The machine learning models demonstrated promising potential for predicting AD biomarkers, emphasizing the need for future research to evaluate their applicability in both clinical and research contexts.
Authors
- Georgios Zisis (ORCID: https://orcid.org/0000-0003-2967-0318)
- Liang Jin (ORCID: https://orcid.org/0000-0001-6464-6263)
- Yihan Wang (ORCID: https://orcid.org/0000-0002-9603-842X)
- Benjamin Goudey (ORCID: https://orcid.org/0000-0002-2318-985X)
- Chenyin Chu
- Liwei Ma
- Colin L. Masters
- Yijun Pan
- Andrew Huynh
Institutions
- The University of Melbourne (AU)
- Florey Institute of Neuroscience and Mental Health (AU)
- Austin Health (AU)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70860_097106
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00