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BioSTORM: a system for automated surveillance of diverse data sources
Martin J O'Connor1, David L Buckeridge, Michael Choy
1Stanford Medical Informatics, Stanford University School of Medicine, CA, USA.
Abstract:
Heightened concerns about bioterrorism are forcing changes to the traditional biosurveillance-model. Public health departments are under pressure to follow multiple, non-specific, pre-diagnostic indicators, often drawn from many data sources. As a result, there is a need for biosurveillance systems that can use a variety of analysis techniques to rapidly integrate and process multiple diverse data feeds using a variety of problem solving techniques to give timely analysis. To meet these requirements, we are developing a new system called BioSTORM (Biological Spatio-Temporal Outbreak Reasoning Module).
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