ITR: A System for Data Integration and Pattern Discovery in Multimodal, Spatio-temporal Data: Lesion Analysis and Data Sharing

我们提出了一个系统，MS分析，分析和检测多发性硬化症（MS）的模式，多发性硬化症是一种脑部疾病，随着疾病的进展，可能导致运动和记忆技能的丧失，甚至死亡。磁共振成像（MRI）用于使用不同的成像方式定期监测大脑变化，并且还测试受试者的运动和认知健康，因为不同的药物治疗被探索以减缓疾病。病理学模式与药物治疗的有效关联需要访问大量的综合数据，而这些数据通常是任何一个特定实验室都无法获得的。MS-Analyze通过将数据收集、数据融合、数据分析和安全数据共享相结合，解决了这两个挑战。拟议的工作将产生表示和管理异构数据流的新方法。它将为数据共享和研究合作、快速模式发现提供新的机制，并为制定共享敏感信息的标准提供试验平台。MS是一个很好的应用程序来演示系统，因为它提供了丰富的数据，挑战系统开发。更广泛的影响：除了解决对数据的直接需求，这个项目还具有强大的教育和培训组件，因为它也是为了培训用户处理MS中的复杂数据而构建的。

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.