Predicting Alzheimer's disease progression using deep recurrent neural networks
Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. In this study, given multimodal AD markers and clinical diagnosis of an individual from one or more timepoints, we seek to predict the clinical di...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-11-01
|
| Series: | NeuroImage |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811920306893 |