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: | Hao Ren |
| Institution: | Shenzhen University |
| Department: | Computer Science |
| Country: | |
| Proposed Analysis: | Alzheimer’s disease (AD) is a complex disorder influenced by many factors, but it is unclear how each factor contributes to disease progression. An in-depth examination of these factors may yield an accurate estimate of time-to-conversion to AD for patients at various disease stages. Recent advances in deep learning have enabled researchers to predict patient’s disease onset time by exploring the influencing factors in AD progression. We want to use a Deep Learning-based survival analysis model that extends the classic Cox regression model to predict the subjects’ disease onset time. Here we re-define the non-AD-progression as “survivor”, and AD-progression as “non-survivor”. The subjects were divided into two groups: progressive subjects (non-survivor), who were either healthy or diagnosed with Mild Cognitive Impairment (MCI) at initial clinical visit and later developed AD, and non-progressive subjects ("survivor”), who were either healthy or MCI at initial visit but did not develop AD later. |
| Additional Investigators |
