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: | Ting Wu |
| Institution: | The First Affiliated Hospital of Nanjing Medical University |
| Department: | Neurology Department |
| Country: | |
| Proposed Analysis: | Alzheimer’s disease is a progressive neurodegenerative disease, the most common cause of dementia. We plan to collect the information of the database to predict whether the cognitive function of patients with Alzheimer's disease is improved before follow-up through machine learning. Then we gradually reduce the variables of model, and finally select the most efficient model without significantly reducing the accuracy. By comparing with the actual results of follow-up, we evaluate the accuracy of the model, so as to guide the clinical treatment plan of patients in advance according to the predicted results. |
| Additional Investigators | |
| Investigator's Name: | Yu Zheng |
| Proposed Analysis: | Alzheimer’s disease is a progressive neurodegenerative disease, the most common cause of dementia. We plan to collect the information of the database to predict whether the cognitive function of patients with Alzheimer's disease is improved before follow-up through machine learning. Then we gradually reduce the variables of model, and finally select the most efficient model without significantly reducing the accuracy. By comparing with the actual results of follow-up, we evaluate the accuracy of the model, so as to guide the clinical treatment plan of patients in advance according to the predicted results. |
| Investigator's Name: | Siyu Yang |
| Proposed Analysis: | Alzheimer’s disease is a progressive neurodegenerative disease, the most common cause of dementia. We plan to collect the information of the database to predict whether the cognitive function of patients with Alzheimer's disease is improved before follow-up through machine learning. Then we gradually reduce the variables of model, and finally select the most efficient model without significantly reducing the accuracy. By comparing with the actual results of follow-up, we evaluate the accuracy of the model, so as to guide the clinical treatment plan of patients in advance according to the predicted results. |
| Investigator's Name: | Xinran Xu |
| Proposed Analysis: | Alzheimer’s disease is a progressive neurodegenerative disease, the most common cause of dementia. We plan to collect the information of the database to predict whether the cognitive function of patients with Alzheimer's disease is improved before follow-up through machine learning. Then we gradually reduce the variables of model, and finally select the most efficient model without significantly reducing the accuracy. By comparing with the actual results of follow-up, we evaluate the accuracy of the model, so as to guide the clinical treatment plan of patients in advance according to the predicted results. |
