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: | Jinling Ji |
| Institution: | University of Edinburgh |
| Department: | School of Informatics |
| Country: | |
| Proposed Analysis: | Developing an interpretable deep learning model for brain health research With the accelerated aging process in European countries, the population of Alzheimer’s patients is increasing year by year. Previous work has developed an interpretable machine learning-based dementia risk prediction model. However, the performance of the target model obtained by transfer learning still has a lot space for improvement. We propose an interpretable deep learning-based dementia risk prediction model to improve the accuracy of model predictions. Use a CNN deep learning model to learn complex relationships between risk factors from the ADNI dataset and the SVM model to predict dementia risk, and use visualization to explain the interactions between risk factors. |
| Additional Investigators |
