Source:http://linkedlifedata.com/resource/pubmed/id/17238486
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Predicate | Object |
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rdf:type | |
lifeskim:mentions | |
pubmed:dateCreated |
2007-1-22
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pubmed:abstractText |
In the wake of fears over pandemic influenza, triggered by concern about avian influenza, a top national priority is to adapt surveillance systems, such as Biosense, for influenza monitoring. While real time surveillance system architects have been largely focused on the problem of discrete outbreak detection, the data in these systems have been shown to have unique advantages for the timely detection of influenza. In this study, we evaluate the utility influenza detection by real-time surveillance as an adjunct to the traditional CDC surveillance systems.
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pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
1942-597X
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pubmed:author | |
pubmed:issnType |
Electronic
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
866
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pubmed:dateRevised |
2009-3-9
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pubmed:meshHeading |
pubmed-meshheading:17238486-Algorithms,
pubmed-meshheading:17238486-Boston,
pubmed-meshheading:17238486-Computer Systems,
pubmed-meshheading:17238486-Disease Outbreaks,
pubmed-meshheading:17238486-Emergency Service, Hospital,
pubmed-meshheading:17238486-Humans,
pubmed-meshheading:17238486-Influenza, Human,
pubmed-meshheading:17238486-Population Surveillance
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pubmed:year |
2006
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pubmed:articleTitle |
Reengineering real time outbreak detection systems for influenza epidemic monitoring.
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pubmed:affiliation |
Children's Hospital Informatics Program at Harvard-MIT Health Sciences and Technology, Harvard Medical School, Boston, MA, USA.
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pubmed:publicationType |
Journal Article,
Comparative Study,
Evaluation Studies
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