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: | Joseph Giorgio |
| Institution: | University of Cambridge |
| Department: | Psychology |
| Country: | |
| Proposed Analysis: | We propose to implement machine learning algorithms with “privileged information” (PI). To address the twin need for (1) training robust models with a comprehensive set of inputs and (2) future prediction based on clinic data alone, we will train metric learning algorithms to classify individuals at high vs. low risk of dementia using multimodal MRI (i.e. structural and functional integrity and connectivity measures) as PI. These data provide prognostically relevant information above and beyond that obtainable from standard clinical practice tools. Following this training phase, the algorithms will be tested in classifying new individual cases from “routine” epidemiological and cognitive data alone that are typically collected at the clinic. This approach has the potential to deliver low-cost robust and sensitive tools of detecting individualized risk of disease that is scalable for widespread implementation in clinical practice. |
| Additional Investigators | |
| Investigator's Name: | zoe kourtzi |
| Proposed Analysis: | same as primary investigator |
| Investigator's Name: | Avraam Papadopoulos |
| Proposed Analysis: | Same as principal investigator |
| Investigator's Name: | Soroosh Afyouni |
| Proposed Analysis: | Same as principal investigator |
| Investigator's Name: | Georgios Batzolis |
| Proposed Analysis: | Same as principal investigator |
