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: | Tess Cersonsky |
| Institution: | Brown University |
| Department: | Medicine |
| Country: | |
| Proposed Analysis: | The goal of this study is to develop a predictive model that can be applied in clinical settings as an early screener for AD risk. Data will be used to develop, validate, and replicate a predictive algorithm to classify early AD risk using machine learning and predictive modeling. We will employ cutting edge statistics and informatics to leverage information across several harmonized datasets for machine learning model training. We will then utilize our own registry data as an independent, replication sample.This research is being conducted as part of an NIH-Funded study: U54GM115677 (Padbury, PI, "Building an Infrastructure and Dynamic Dataset for AD Risk Assessment, extension for Institutional Development Award for Clinical and Translational Research (IDeA-CTR) from the NIGMS. |
| Additional Investigators |
