Deep Learning Model for Forecasting Propagation of Amyloidopathy in Alzheimer’s Disease
We introduced a deep learning model that simulates the diffusion of amyloid-β with strong predictive performance and interpretation. While parameters were optimized for the entire group, accuracy varied for some subjects. Also, further investigation is needed to interpret each term comprehensively. Despite the need for individual optimization and additional interpretative analysis, the model may contribute to the diagnosis of AD.
Authors
- Hyun‐Ghang Jeong (ORCID: https://orcid.org/0000-0002-0318-5069)
- Cheol E. Han (ORCID: https://orcid.org/0000-0002-9994-6861)
- ByeongChang Jeong
- Surin Seo (ORCID: https://orcid.org/0000-0003-2892-5753)
- Seung‐Hoon Lee (ORCID: https://orcid.org/0000-0001-5341-0933)
- Daegyeom Kim (ORCID: https://orcid.org/0009-0003-8573-8820)
Institutions
- Korea University (KR)
- Korea University Medical Center (KR)
- Sejong University (KR)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/alz.085828
- Primary Topic
- Alzheimer's disease research and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00