Displaying results 1 - 8 of 9
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Detection of Patients with Influenza Syndrome Using Machine-Learning Models Learned from Emergency Department Reports
Content Type: Abstract
Early detection of influenza outbreaks is critical to public health officials. Case detection is the foundation for outbreak detection. Previous study by Elkin el al. demonstrated that using individual emergency department (ED) reports can better… read more -
Modeling Baseline Shifts in Multivariate Disease Outbreak Detection
Content Type: Abstract
Population surges or large events may cause shift of data collected by biosurveillance systems [1]. For example, the Cherry Blossom Festival brings hundreds of thousands of people to DC every year, which results in simultaneous elevations in… read more -
Ellipse-Based Clustering Analysis Using a Time Series Algorithm
Content Type: Abstract
Many cities in the US and the Center for Disease Control and Prevention have deployed biosurveillance systems to monitor regional health status. Biosurveillance systems rely on algorithms that analyze data in temporal domain… read more -
Monitoring Pharmacy Retail Data for Anomalous Space-Time Clusters
Content Type: Abstract
Bio-surveillance systems monitor multiple data streams (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. influenza) and bio-terrorist attacks (e.g. anthrax re-lease). Many detection… read more -
Building an automated Bayesian case detection system
Content Type: Abstract
Current practices of automated case detection fall into the extremes of diagnostic accuracy and timeliness. In regards to diagnostic accuracy, electronic laboratory reporting (ELR) is at one extreme and syndromic surveillance is at… read more -
Challenges in adapting an natural language processing system for real-time surveillance
Content Type: Abstract
We are developing a Bayesian surveillance system for realtime surveillance and characterization of outbreaks that incorporates a variety of data elements, including free-text clinical reports. An existing natural language processing (… read more -
A data simulation model using NRDM pharmaceutical sales counts
Content Type: Abstract
In disease surveillance, an outbreak is often present in more than one data type. If each data type is analyzed separately rather than combined, the statistical power to detect an outbreak may suffer because no single data source… read more -
An automated influenza-like-illness reporting system using freetext emergency department reports
Content Type: Abstract
Current methods for influenza surveillance include laboratory confirmed case reporting, sentinel physician reporting of Influenza-Like-Illness (ILI) and chief-complaint monitoring from emergency departments (EDs). The current… read more