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: | yi zhang |
| Institution: | University of Goettingen |
| Department: | Department of Animal Science |
| Country: | |
| Proposed Analysis: | Machine Learning methods have effectively identified genetic factors for many diseases. Many diseases, including Alzheimer’s disease (AD), have epistatic causes, requiring more sophisticated analyses to identify groups of variants which together affect phenotype. Based on conventional machine learning methods, we developed a novel graph based semi-supervised learning model to identify pairs of variants whose common occurrence signaled the Alzheimer’s disease phenotype, and to predict the individual genetic risk of Alzheimer’s disease occurrence. We hope it is possible to validate our model by using the datasets from AIBL, ADNI and ADNIDOD. |
| Additional Investigators |
