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: | Edward Vendrow |
| Institution: | Stanford University |
| Department: | Computer Science |
| Country: | |
| Proposed Analysis: | In this project, we seek to develop Machine Learning based tools to 1. Predict if a patient has the disease 2. Predict how a patient will respond to common dementia delaying drugs (will their cognition improve?) 3. Predict which areas of a patient’s brain are most at risk (personalized medicine). For Aim 1, we plan to use logistic regression, Multinomial Naive Bayes (mNB), Stochastic Gradient Descent Support Vector Machine (SVM), and Deep Convolutional Neural Networks (CNN) to classify given a brian slice if it is (1) Alzheimer’s Disease or (0) Cognitively Normal. For Aim 2, the model is trained to make a binary prediction for a patient with early Alzheimer’s if they will have better or worse cognitive scores in follow up visits (same input as Aim 1) For Aim 3, the model is trained to output which one of 27 brain regions is most affected by AD as measured by volume decline between MRI sessions. |
| Additional Investigators | |
| Investigator's Name: | Ethan Schonfeld |
| Proposed Analysis: | In this project, we seek to develop Machine Learning based tools to 1. Predict if a patient has the disease 2. Predict how a patient will respond to common dementia delaying drugs (will their cognition improve?) 3. Predict which areas of a patient’s brain are most at risk (personalized medicine). |
