Enhancing Time-Series Detection Algorithms for Automated Biosurveillance
نویسندگان
چکیده
منابع مشابه
Enhancing Time-Series Detection Algorithms for Automated Biosurveillance
BioSense is a US national system that uses data from health information systems for automated disease surveillance. We studied 4 time-series algorithm modifications designed to improve sensitivity for detecting artificially added data. To test these modified algorithms, we used reports of daily syndrome visits from 308 Department of Defense (DoD) facilities and 340 hospital emergency department...
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National syndromic surveillance systems require optimal anomaly detection methods. For method performance comparison, we injected multi-day signals stochastically drawn from lognormal distributions into time series of aggregated daily visit counts from the U.S. Centers for Disease Control and Prevention's BioSense syndromic surveillance system. The time series corresponded to three different sy...
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ژورنال
عنوان ژورنال: Emerging Infectious Diseases
سال: 2009
ISSN: 1080-6040,1080-6059
DOI: 10.3201/1504.080616