| Download | - View final version: Detecting outbreaks in time-series data with RecentMax (PDF, 554 KiB)
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| DOI | Resolve DOI: https://doi.org/10.5210/ojphi.v7i1.5779 |
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| Author | Search for: Carter, Dave1; Search for: Martin, Joel D.1 |
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| Affiliation | - National Research Council Canada. Information and Communication Technologies
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| Format | Text, Abstract |
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| Conference | 2014 ISDS Conference: International Society for Disease Surveillance, December 9 - 11, 2014, Philadelphia, PA, USA |
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| Subject | aberration detection; algorithm; outbreak detection; surveillance; situational awareness |
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| Abstract | The 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. |
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| Publication date | 2015 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23000531 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 26726661-96b6-4580-8d40-2327b5070cd1 |
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| Record created | 2016-07-28 |
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| Record modified | 2020-06-02 |
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