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: | Sasha Bonacina |
| Institution: | University of Bristol |
| Department: | Engeneering Maths |
| Country: | |
| Proposed Analysis: | Diverse types of biomarkers are reported in research on Alzheimer's Disease and related dementias. The existence of these biomarkers may begin many years before symptoms appear. Hence, finding these biomarkers early in the disease helps identify people who are at the greatest risk of Alzheimer's or other dementia and may help determine which people might benefit most from a particular treatment. In this project, we aim to use machine learning approaches to investigate and identify biomarkers at the early stages of Alzheimer’s Disease. Most of the biomarkers investigated in the literature are related to imaging including MRI and PET scans. Little attention has been given to biomarkers on genomic data, which are not routinely used for dementia-related diseases. This project will aim first to investigate the biomarkers related to genomic data and identify their importance to early diagnosis of the disease using machine learning approaches. Then, that will be followed by investigating and validating the value of combining identified biomarkers from different sources using a multi-modality approach. The data to be used for this project is provided by Alzheimer’s Disease Neuroimaging Initiative (ADNI) http://adni.loni.usc.edu/ . The data repository contains imaging, clinical, and genetic data for over 2220 patients. ADNI aims to test whether serial MRI, PET, biological markers, and clinical and neuropsychological assessments can be combined to measure the progression of mild cognitive disorders and early diagnosis of Alzheimer’s disease. |
| Additional Investigators |
