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: | Jan Ernsting |
| Institution: | University of Münster |
| Department: | Institute for Translational Psychiatry |
| Country: | |
| Proposed Analysis: | The brain-age gap is one of the most investigated risk markers for cross-disorder brain changes. While the field is beginning to recognize the importance of quantifying uncertainty of predictions for group-level inference, no models to date provide single-subject risk assessment as needed for clinical application. Here, we present a novel framework combining neural network models with uncertainty methods. This combination will lead to more sophisticated approaches for detection and definition of accelerated brain aging. We aim to 1. provide means to define accelerated brain aging, 2. build models containing methods to provide statistically provable guarantees for the predicted uncertainty intervals, and 3. build a longitudinal approach on top of these insights to further investigate the effect of brain-age deviation. As mild cognitive impairment (MCI) and Alzheimer's disease (AD) have been shown to be associated with brain-age, we would like to test and develop our methods on the ADNI Dataset. |
| Additional Investigators |
