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: | xiao Chen |
| Institution: | Minjiang University |
| Department: | College of Mathematics and Data Science (Software |
| Country: | |
| Proposed Analysis: | The ADNI (Alzheimer's Disease Neuroimaging Initiative) database is a valuable resource for conducting research on Alzheimer's disease. One potential analysis that could be performed using this database is the development of a predictive model for Alzheimer's disease diagnosis. To perform this analysis, we would start by selecting a subset of the ADNI database that includes individuals with a confirmed Alzheimer's disease diagnosis as well as a control group of individuals without the disease. We would then use machine learning techniques to identify features that are predictive of Alzheimer's disease, such as brain imaging data, cognitive assessments, and genetic information. Next, we would use these features to train a predictive model that can accurately classify individuals as either having or not having Alzheimer's disease. We would evaluate the performance of the model using metrics such as sensitivity, specificity, and area under the curve. The ultimate goal of this analysis would be to develop a tool that can aid in the early diagnosis of Alzheimer's disease. By identifying individuals who are at high risk of developing the disease before symptoms appear, we may be able to intervene earlier and potentially slow or even halt disease progression. In summary, the proposed analysis would use the ADNI database to develop a predictive model for Alzheimer's disease diagnosis, with the ultimate goal of improving early detection and intervention for this devastating disease. |
| Additional Investigators |
