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: | Xuan Gu |
| Institution: | Linköping University |
| Department: | National Supercomputer Centre |
| Country: | |
| Proposed Analysis: | The main objective of this research proposal is to develop a deep learning-based approach for predicting cognitive decline in Alzheimer's Disease using ADNI MRI data. Specifically, we aim to: 1. Develop a deep learning model to classify AD and non-AD individuals using MRI images. 2. Investigate the relationship between MRI biomarkers and cognitive decline in AD. 3. Develop a model to predict cognitive decline in AD using MRI images. We plan to use a combination of convolutional neural networks (CNN) and recurrent neural networks (RNN) to develop a deep learning model for classification of AD and non-AD individuals. We will use transfer learning techniques to fine-tune pre-trained CNN models on ADNI MRI images. We will also develop a multi-task RNN model that simultaneously predicts cognitive decline and classifies AD and non-AD individuals using MRI images. We will evaluate the performance of the models using metrics such as accuracy, sensitivity, specificity, and area under the curve (AUC). |
| Additional Investigators |
