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: | Yuan Luo |
| Institution: | Northwestern University |
| Department: | Preventive Medicine |
| Country: | |
| Proposed Analysis: | In this proposal, we will specifically focus on further developing and validating our methods for computational phenotyping and its application for Alzheimer’s Disease (AD) research. Specifically, we will develop machine learning methods for identification of AD sub-phenotypes. On patients diagnosed with AD, we will retrospectively review their features from ADNI and develop machine learning methods for computationally deriving AD sub-phenotypes based on tensor factorization. Our hypothesis is that patients with AD sub-phenotypes will be heterogeneous with respect to age at onset, socioeconomic status, rate of progression and other clinical features. This supplement, if funded, will provide insights into how a data-driven approach can help identify AD patients eligible for prospective clinical trials. |
| Additional Investigators |
