There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Vishal Saxena |
| Institution: | University of Delaware |
| Department: | Electrical and Computer Engineering |
| Country: | |
| Proposed Analysis: | Alzheimer’s disease (AD), is a progressive neurodegenerative disease characterized by damage to neurons and their connections leading to memory loss and cognitive decline. Currently no known interventions will cure AD, however most drugs are targeted at early or middle stages of the disease. Hence, it is imperative to diagnose AD at earlier stages. ADNI dataset provides multimodal data including clinical cognitive scores and MRI images. The goal of this research is to explore deep neural network architectures for developing a framework for prediction of AD from multimodal data. This problem is particularly challenging as this is a small and multimodal dataset which will require fusion from neural networks that individually perform classification on images and numerical scores. Of particular interest is using spiking neural networks for energy-efficient and low latency classification, and semi-supervised learning methods. |
| Additional Investigators |
