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: | Arin Kathapurkar |
Institution: | Merryhill School |
Department: | 8th grade |
Country: | |
Proposed Analysis: | Our project with the ADNI data is to create an algorithm that detects Alzheimer's before it stems in patients and predicts when it will be diagnosed in patients. With the ADNI data, we can train the AI with examples. We plan to train the AI to pick up on common markers throughout the data. Once the AI is trained, it should execute the algorithm using data that was not in the training set, and it should show when (if) a person will be diagnosed with Alzheimer's disease. This is what we would like to do with the ADNI data. |
Additional Investigators | |
Investigator's Name: | Harsha Manamala |
Proposed Analysis: | Our plan is to create an algorithm to predict if and when a person will have / be diagnosed with Alzheimers Diesease. Using the data, we will train the AI to pick up on common markers throughout the data. Once the AI is trained, it should be able to tell when (if) a person will have Alzheimers diesease. For example if we train the AI, and we input the data of Patient A, the AI should be able to use the data and output when the person was diagnosed with Alzheimers Diesease. |
Investigator's Name: | Harsha Manamala |
Proposed Analysis: | Our plan is to create an algorithm to predict if and when a person will have / be diagnosed with Alzheimers Diesease. Using the data, we will train the AI to pick up on common markers throughout the data. Once the AI is trained, it should be able to tell when (if) a person will have Alzheimers diesease. For example if we train the AI, and we input the data of Patient A, the AI should be able to use the data and output when the person was diagnosed with Alzheimers Diesease. |
Investigator's Name: | Jay Gokani |
Proposed Analysis: | Our plan is to create an algorithm to predict if and when a person will have / be diagnosed with Alzheimers Diesease. Using the data, we will train the AI to pick up on common markers throughout the data. Once the AI is trained, it should be able to tell when (if) a person will have Alzheimers diesease. For example if we train the AI, and we input the data of Patient A, the AI should be able to use the data and output when the person was diagnosed with Alzheimers Diesease. |