White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer’s disease
The present results demonstrate that a joint model combining neuropsychological scales can be constructed by using machine learning and DTI technology to identify MCI patients who are at high-risk of progressing to AD.
Authors
- Lu Han (ORCID: https://orcid.org/0000-0002-4465-9590)
- Zhongyu Yuan (ORCID: https://orcid.org/0009-0005-5545-3925)
- Jiaxuan Peng (ORCID: https://orcid.org/0000-0002-1455-1706)
- Yang Zhang (ORCID: https://orcid.org/0000-0001-9290-5891)
- Zihan Zhang (ORCID: https://orcid.org/0000-0002-5912-2497)
- Zhenyu Shu (ORCID: https://orcid.org/0000-0002-7529-2357)
- Yuyun Xu (ORCID: https://orcid.org/0000-0003-2818-852X)
- Guangying Zheng (ORCID: https://orcid.org/0000-0002-3105-5579)
- Mengmeng Hu (ORCID: https://orcid.org/0009-0005-9918-267X)
- Yuan Shao
- Xiaokai Gu
- Xiaojun Sun
Institutions
- Zhejiang Provincial People's Hospital (CN)
- Hangzhou Medical College (CN)
- Zhejiang University of Technology (CN)
- Jinzhou Medical University (CN)
Publication Details
- Journal
- BMC Geriatrics
- Published
- 2024-08-19
- DOI
- https://doi.org/10.1186/s12877-024-05293-7
- Citations
- 6
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 2.31
Funders
- Alzheimer's Association
- Bristol-Myers Squibb
- Eli Lilly and Company
- Pfizer
- Biogen
- University of Southern California
- Meso Scale Diagnostics
- Alzheimer's Disease Neuroimaging Initiative
- BioClinica
- Novartis Pharmaceuticals Corporation
- Northern California Institute for Research and Education
- National Natural Science Foundation of China
- Eisai
- Servier
- H. Lundbeck A/S
- IXICO
- National Institutes of Health
- Genentech
- Canadian Institutes of Health Research
- Natural Science Foundation of Zhejiang Province