Displaying results 1 - 8 of 18
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A Case Manager Tool for Anomaly Investigation in BioSurveillance
Content Type: Abstract
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… read more -
A Pilot Study of Aberration Detection Algorithms with Simulated Data
Content Type: Abstract
To evaluate four algorithms with varying baseline periods and adjustment for day of week for anomaly detection in syndromic surveillance data. read more -
A System for Simulation: Introducing Outbreaks into Time Series Data
Content Type: Abstract
Objective Several authors have described ways to introduce artificial outbreaks into time series for the purpose of developing, testing, and evaluating the effectiveness and timeliness of anomaly detection algorithms, and more… read more -
An Adaptive Anomaly Detection Algorithm
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… read more -
Performance of an Adaptive Anomaly Detection Algorithm for a Low Incidence Syndrome Before and After a Major Outbreak
Content Type: Abstract
Ideal anomaly detection algorithms should detect both sudden and gradual changes, while keeping the background false positive alert rate at a tolerable level. Further, the algorithm needs to perform well when the need is to detect… read more -
Performance of Sub-Syndrome Chief Complaint Classifiers for the GI Syndrome
Content Type: Abstract
The Centers for Disease Control and Prevention BioSense project has developed chief complaint (CC) and ICD9 sub-syndrome classifiers for the major syndromes for early event detection and situational awareness. This has the potential to… read more -
Improvement in Performance of Ngram Classifiers with Frequent Updates
Content Type: Abstract
Syndromic surveillance of emergency department(ED) visit data is often based on computerized classifiers which assign patient chief complaints (CC) tosyndromes. These classifiers may need to be updatedperiodically to account for changes… read more -
Investigating Syndromic Peaks Using Remotely Available Electronic Medical Records
Content Type: Abstract
One limitation of syndromic surveillance systems based on emergency department (ED) data is the time and expense to investigate peak signals, especially when that involves phone calls or visits to the hospital. Many EDs use electronic medical… read more