@article{ref1,
title="BioSTORM: a system for automated surveillance of diverse data sources",
journal="AMIA annual symposium proceedings",
year="2003",
author="O'Connor, Martin J. and Buckeridge, David L. and Choy, Michael and Crubezy, Monica and Pincus, Zachary and Musen, Mark A.",
volume="ePub",
number="ePub",
pages="1071-1071",
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).<p /><p>Language: en</p>",
language="en",
issn="1559-4076",
doi="",
url="http://dx.doi.org/"
}