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Effective anomaly detection depends on the timely, asynchronous generation of anomalies from multiple data streams using multiple algorithms. Our objective is to describe the use of a case manager tool for combining anomalies into cases, and for collaborative investigation and disposition of... Read more

Content type: Abstract

Ideal anomaly detection algorithms shoulddetect both sudden and gradual changes, while keeping the background false positive alert rate at a tolerable level. The algorithms should also be easy to use. Our objective was to develop an anomaly detection algorithm that adapts to the time series... Read more

Content type: Abstract

Syndromic surveillance of emergency department (ED) visit data is often based on computer algorithms which assign patient chief complaints (CC) and ICD code data to syndromes. The triage nurse note (NN) has also been used for surveillance. Previously we developed an “NGram” classifier for... Read more

Content type: Abstract

The Centers for Disease Control and Prevention BioSense has developed chief complaint (CC) and ICD9 sub syndrome classifiers for the major syndromes for early event detection and situational awareness. The prevalence of these sub-syndromes in the emergency department population and the ... Read more

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