Detecting outbreaks in time-series data with RecentMax

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DOIResolve DOI: http://doi.org/10.5210/ojphi.v7i1.5779
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TypeAbstract
Proceedings titleOnline Journal of Public Health Informatics
Conference2014 ISDS Conference: International Society for Disease Surveillance, December 9 - 11, 2014, Philadelphia, PA, USA
ISSN1947-2579
1947-2579
Volume7
Issue1
Article numbere113
Subjectaberration detection; algorithm; outbreak detection; surveillance; situational awareness
AbstractThe RecentMax algorithm seeks to detect typical outbreaks of transmissible disease (particularly influenza-like illness) in time-series data better than existing algorithms like CDC EARS C1/C2/C3.
Publication date
PublisherUniversity of Illinois at Chicago Library
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number23000531
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Record identifier26726661-96b6-4580-8d40-2327b5070cd1
Record created2016-07-28
Record modified2016-07-28
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