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: | Won Hee Lee |
| Institution: | Kyung Hee University |
| Department: | Software Convergence |
| Country: | |
| Proposed Analysis: | The brain-predicted age difference (brainPAD) is considered a personalized marker of brain health as it quantified the divergence between the chronological and biological age of the brain of an individual as predicted from neuroimaging data. Individual variation in brainPAD has been associated with multiple behavioral and health features. We aim to use multimodal (T1, T2, DTI, fMRI) ADNI datasets to undertake a comprehensive evaluation of the associations between brainPAD and a wide range of cognitive (behavioral) datasets. Automatic machine learning algorithms will be applied to the features extracted from multimodal neuroimaging datasets in order to estimate the brainPAD. We will evaluate the performance of different machine learning algorithms in terms of correlation analyses and hierarchical clustering. The association between brainPAD and cognitive (behavioral) measures will be examined. |
| Additional Investigators |
