title: BioSTORM: a system for automated surveillance of diverse data sources.
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).
authors.affiliation: Stanford Medical Informatics, Stanford University School of Medicine, CA, USA.
authors.forename: Martin J
authors.initials: MJ
authors.lastname: O'Connor
authors.forename: David L
authors.initials: DL
authors.lastname: Buckeridge
authors.forename: Michael
authors.initials: M
authors.lastname: Choy
authors.forename: Monica
authors.initials: M
authors.lastname: Crubezy
authors.forename: Zachary
authors.initials: Z
authors.lastname: Pincus
authors.forename: Mark A
authors.initials: MA
authors.lastname: Musen
mesh_terms: D023482:Bioterrorism; D003625:Data Collection; D004196:Disease Outbreaks; D006801:Humans; D007256:Information Systems; D011159:Population Surveillance / Q000379:methods*