We propose a system, MS-Analyze, to analyze and detect patterns in Multiple Sclerosis (MS), a brain disease that can lead to loss of motor and memory skills and even death, as the disease progresses over time. Magnetic Resonance Imaging (MRI) is used to monitor brain changes at regular time intervals using different imaging modalities, and subjects are also tested for their motor and cognitive fitness, as different drug treatments are explored to slow the disease. Effective correlation of patterns in pathology with drug treatments requires access to large amounts of integrated data, which is usually not available to any one given laboratory. MS-Analyze addresses both of these challenges by combining data collection, data fusion, data analysis, and secure data sharing. The proposed work will generate new methods of representing and managing heterogeneous data streams. It will provide new mechanisms for data sharing and research collaboration, fast pattern discovery and a testbed for developing standards for sharing sensitive information. MS is a good application to demonstrate the system because it offers rich data that challenge the system development. Broader Impact: Aside from solving the immediate need for data, this project also has a strong educational and training component as it is built also to train users in dealing with complex data as in MS.
