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: | Anthony Tran |
| Institution: | California Polytechnic State University, Pomona |
| Department: | Business and Technology |
| Country: | |
| Proposed Analysis: | Alzheimer’s Dementia (AD), which is the most common type of dementia, accounts for nearly 60% to 70% of all dementia cases, causing loss of memory and behavioral changes. One way to mitigate the progressive damages of AD is early identification of AD so treatment can start as soon as possible. This study aims to determine whether machine learning technology can be incorporated into the field of medicine and reliably predict AD. To do this, A CNN imagine structure will be created using the given ADNI scans. First, the images will be preprocessed. Then, a kernel will slide through the each of the images layers. Max and average values will be pooled and a ReLU activation function will be applied to mitigate overfitting. By the end, the CNN algorithm will be trained and the AI will have identified features to be able to predict AD in a given image with at least a 75% prediction rate. This research will prove that AI and advanced machine learning technology can be used reliably in medicine since computers can process information and data at a much faster rate than humans, as well as have a high capacity of memory and storage. The field of neurology will be greatly improved with this research. Currently, the CNN model has been built to an acceptable degree for image processing using random test images online, not related to AD, as a proof of concept. The limitations of this research is time constraint since the deadline May 19, 2023. |
| Additional Investigators |
