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Organizing and annotating biomedical data in structured ways has gained much interest and focus in the last 30 years. Driven by decreases in digital storage costs and advances in genetics sequencing, imaging, electronic data collection, and microarray technologies, data is being collected at an ever increasing rate. The need to store and exchange data in(More)
Managing vast datasets collected throughout multiple clinical imaging communities has become critical with the ever increasing and diverse nature of datasets. Development of data management infrastructure is further complicated by technical and experimental advances that drive modifications to existing protocols and acquisition of new types of research data(More)
——Biomedical research increasingly depends on access to and analysis of distributed medical and biomedical data. In biomedical research, datasets are often collected at multiple locations, as it is difficult to recruit required patient populations at one location. The sensitive nature of these datasets leads to a need for secure sharing methods that can(More)
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