Predicting Parkinson's Disease Using a Highly Accurate Convolutional Neural Network

Started Aug. 31, 2021

Abstract or project description

To accurately diagnose Parkinson's Disease using image data, we are going to gather datasets from PPMI and BioFIND. The data will be plugged into a Convolutional Neural Network as that has been found to have the highest accuracy with regard to image data. PPMI and BioFIND both have thorough quantitative data and image data, so it is possible to make a second model that processes quantitative data. Therefore, the user is given the ability to chose which type of data they would find easiest to input.