Predicting positron emission tomography brain amyloid positivity using wearable sensor data and lifestyle factors
Our machine learning models are useful for predicting elevated brain amyloid burden for MCI patients using readily-available and noninvasive variables without the need to visit a hospital.
Authors
- Ken Aoshima (ORCID: https://orcid.org/0000-0001-7640-6005)
- Teruaki Masuda (ORCID: https://orcid.org/0000-0001-9730-3339)
- Kotaro Sasaki (ORCID: https://orcid.org/0009-0007-3081-9438)
- Noriyuki Kimura
Institutions
- University of Tsukuba (JP)
- Oita University (JP)
- Eisai (Japan) (JP)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_100717
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00