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: | Xin Chen |
| Institution: | University of Nottingham |
| Department: | School of Computer Science |
| Country: | |
| Proposed Analysis: | An increasing number of studies have shown that longitudinal imaging data taken at different time points significantly contribute to diagnoses of complicated and chronic diseases (e.g. Alzheimer’s disease, multiple sclerosis) or used as a surrogate for monitoring treatment responses (e.g. chemotherapy in cancer treatment). To date, effective and consistent feature extraction from variable numbers of longitudinal images has not been adequately investigated. In this study, we propose a generic deep learning based framework taking advantage of longitudinal imaging features as well as numerical clinical assessments (medication, phenotype, etc.) for disease diagnosis and clinical outcome prediction. |
| Additional Investigators |
