Displaying results 1 - 3 of 3
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Cloud Computing for Syndromic Surveillance
Content Type: Abstract
Two significant barriers to greater use of syndromic surveillance techniques are computational time and software complexity. Computational time refers to the time for many methods (for example, scan statistics and AMOEBA statistics) to create… read more -
Interactive Detection of Spatial Clusters
Content Type: Abstract
Geographic visualization methods allow analysts to visually discover clusters in multivariate, spatially-referenced data. Computational and statistical cluster detection techniques can automatically detect spatial clusters of high values of a… read more -
Cluster Detection Comparison in Syndromic Surveillance
Content Type: Abstract
The New York City Department of Health and Mental Hygiene (NYC DOHMH) collects data daily from 50 of 61 (82%) emergency departments (EDs) in NYC representing 94% of all ED visits (avg daily visits ~10,000). The information… read more