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: | liwei che |
| Institution: | The Pennsylvania State University |
| Department: | College of Information Science and Technology |
| Country: | |
| Proposed Analysis: | We aim to build a federated learning system to resolve the multimodality and data imbalance challenges for the collaboration for algorithm-assisted diagnosis among the hospitals and medical centers. This system has the purpose to provide decision support for the patient diagnosis with the assistance of AI models. As a longitudinal multicenter study that collected data with multiple modalities, the ADNI dataset perfectly matched the expectations of our project's benchmark dataset. Successfully approving our access to the ADNI dataset will significantly benefit our research. |
| Additional Investigators | |
| Investigator's Name: | Fenglong Ma |
| Proposed Analysis: | We aim to build a federated learning system to resolve the multimodality and data imbalance challenges for the collaboration for algorithm-assisted diagnosis among the hospitals and medical centers. This system has the purpose to provide decision support for the patient diagnosis with the assistance of AI models. As a longitudinal multicenter study that collected data with multiple modalities, the ADNI dataset perfectly matched the expectations of our project's benchmark dataset. Successfully approving our access to the ADNI dataset will significantly benefit our research. |
| Investigator's Name: | Jiaqi Wang |
| Proposed Analysis: | We aim to build a federated learning system to resolve the multimodality and data imbalance challenges for the collaboration for algorithm-assisted diagnosis among the hospitals and medical centers. This system has the purpose to provide decision support for the patient diagnosis with the assistance of AI models. As a longitudinal multicenter study that collected data with multiple modalities, the ADNI dataset perfectly matched the expectations of our project's benchmark dataset. Successfully approving our access to the ADNI dataset will significantly benefit our research. |
| Investigator's Name: | Zewei Long |
| Proposed Analysis: | We aim to build a federated learning system to resolve the multimodality and data imbalance challenges for the collaboration for algorithm-assisted diagnosis among the hospitals and medical centers. This system has the purpose to provide decision support for the patient diagnosis with the assistance of AI models. As a longitudinal multicenter study that collected data with multiple modalities, the ADNI dataset perfectly matched the expectations of our project's benchmark dataset. Successfully approving our access to the ADNI dataset will significantly benefit our research. |
