TY - JOUR
T1 - Ontology-centered syndromic surveillance for bioterrorism
AU - Crubézy, Monica
AU - O'Connor, Martin
AU - Pincus, Zachary
AU - Musen, Mark A.
AU - Buckeridge, David L.
N1 - Funding Information:
This article was supported by DARPA under a national research program for biosurveillance technology. We presented a preliminary version of this article at the 2005 AAAI Spring Symposium on AI Technologies for Homeland Security. We thank our anonymous reviewers for their insightful comments.
PY - 2005/9
Y1 - 2005/9
N2 - The use of ontologies to model and annotate syndromic surveillance information and knowledge is described. Ontologies are computer-stored specifications of concepts, properties, and relationships that are important for describing an area of expertise. It is observed that BioStorm can help by supporting ontology based data integration and problem-solver deployment. BioStorm demonstrates an end-to-end solution to many problems associated with data acquisition, integration, and analysis for public health surveillance.
AB - The use of ontologies to model and annotate syndromic surveillance information and knowledge is described. Ontologies are computer-stored specifications of concepts, properties, and relationships that are important for describing an area of expertise. It is observed that BioStorm can help by supporting ontology based data integration and problem-solver deployment. BioStorm demonstrates an end-to-end solution to many problems associated with data acquisition, integration, and analysis for public health surveillance.
UR - http://www.scopus.com/inward/record.url?scp=27344447612&partnerID=8YFLogxK
U2 - 10.1109/MIS.2005.91
DO - 10.1109/MIS.2005.91
M3 - Review article
AN - SCOPUS:27344447612
SN - 1541-1672
VL - 20
SP - 26
EP - 35
JO - IEEE Intelligent Systems
JF - IEEE Intelligent Systems
IS - 5
ER -