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: | Wenxin Jin |
| Institution: | University of Chinese Academy of Sciences |
| Department: | School of Computer Science and Technology |
| Country: | |
| Proposed Analysis: | Our laboratory is working on AD auxiliary diagnosis and risk assessment based on brain age estimation. This dataset may be very useful for us. Predicting chronological age based on brain magnetic resonance imaging (MRI) data has received growing attention for its potential clinical and biological relevance. The predicted age is considered to be the "brain age", because it is derived purely from the brain imaging data. Over the years, researchers have found that brain age is expected to be an important biomarker of the neuroanatomical aging processes, which can provide risk-assessments and predictions for age-associated neurodegenerative and neuropsychiatric diseases at a single-subject level. Brain age has a wide application in Alzheimer's disease, such as analyzing the longitudinal changes of individual brain aging in AD, the effects of APOE-Genotype on longitudinal changes in AD, and so on. In our reseach, we plan to build deep neural networks to extract high-level features from brain MRI data and predict the chronological age. We will apply our model to the auxiliary diagnosis of Alzheimer's disease and other neuropsychiatric and neurodegenerative diseases. |
| Additional Investigators |
