Prediction of varied brain disorders using massive data sets in imaging and
genomics 
   Lead Investigator:    Gabriel Musso
   Institution      :    RTDS Inc.
   E-Mail           :    gabriel@rtdsinc.com
   Proposal ID      :    742



   Proposal Description:
   Our objective is to use our core technology, which includes imaging and genomics processing pipelines, for predictive modeling and real-time disease diagnosis. Specifically, our core technology allows us to establish a small memory footprint from imaging and genomics data, allowing quick and efficient development of nuanced diagnostic models using massive amounts of patient data. We hope to use the NACC database to create comprehensive disease models using as inclusive a dataset as possible, allowing more holistic diagnostic prediction. The more data can be included, the better the models, and ultimately, the stronger the predictions. These pipelines can then be used by other researchers and organizations to cut down the time spent on preprocessing, feature extraction, and predictive modeling, resulting in faster and more accurate diagnosis using an ever expanding repertoire of patient information.