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: | 昱峥 杜 |
| Institution: | Shandong University of Traditional Chinese Medicine |
| Department: | School of Intelligence and Information Engineering |
| Country: | |
| Proposed Analysis: | This study aims to use machine learning and deep learning algorithms to construct a clinical intelligent non-invasive assisted diagnosis model. Taking advantage of the continuous enrichment of neuroimaging data, researchers use neural imaging training deep learning networks such as MRI and PET to achieve the classification of subjects at multiple stages such as NC, MCI, and AD. This study combines the method of transfer learning and multi-task learning in convolutional neural networks to improve the auxiliary diagnostic accuracy of Alzheimer's disease and the accuracy of early prediction, and if necessary, a variety of neural network combination methods are used to achieve the premise of achieving experimental purposes is that a large number of subjects are required MRI and PET data, and it is hoped that based on the pass, it will be very grateful to make a modest contribution to the diagnosis and research of Alzheimer's disease. |
| Additional Investigators | |
| Investigator's Name: | 妍妍 冯 |
| Proposed Analysis: | This study aims to use machine learning and deep learning algorithms to construct a clinical intelligent non-invasive assisted diagnosis model. Taking advantage of the continuous enrichment of neuroimaging data, researchers use neural imaging training deep learning networks such as MRI and PET to achieve the classification of subjects at multiple stages such as NC, MCI, and AD. This study combines the method of transfer learning and multi-task learning in convolutional neural networks to improve the auxiliary diagnostic accuracy of Alzheimer's disease and the accuracy of early prediction, and if necessary, a variety of neural network combination methods are used to achieve the premise of achieving experimental purposes is that a large number of subjects are required MRI and PET data, and it is hoped that based on the pass, it will be very grateful to make a modest contribution to the diagnosis and research of Alzheimer's disease. |
