Displaying results 9 - 16 of 75
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Comparison of Regression Models with Modified Time Series Methods for BioSurveillance
Content Type: Abstract
To compare regression models with the modified C2 algorithm for analysis of time series data and real time outbreak detection. -
Data-Adapted Temporal Alerting Algorithms for Routine Health Monitoring
Content Type: Abstract
This paper discusses selection of temporal alerting algorithms for syndromic surveillance to achieve reliable detection performance based on statistical properties and the epidemiological context of the input data. We used quantities calculated from… read more -
Data-Adaptive Multivariate Control Charts for Routine Health Monitoring
Content Type: Abstract
This paper investigates the use of data-adaptive multivariate statistical process control (MSPC) charts for outbreak detection using real-world syndromic data. The widely used EARS [1] methods and other adaptive implementations assume implicitly… read more -
Development and Evaluation of a Data-adaptive Algorithm for Univariate Temporal Biosurveillance Data
Content Type: Abstract
Numerous recent papers have evaluated algorithms for biosurveillance anomaly detection. Common essential problems in the disparate, evolving data environment include trends, day-of-week effects, and other systematic behavior.… read more -
Essential Requirements for Effective Advanced Disease Surveillance
Content Type: Abstract
Advanced surveillance systems require expertise from the fields of medicine, epidemiology, biostatistics, and information technology to develop a surveillance application that will automatically acquire, archive, process and present data to the user… read more -
Evaluation of Alerting Sparse-Data Streams of Population Healthcare-Seeking Data
Content Type: Abstract
Objective This presentation discusses the problem of detecting small-scale events in biosurveillance data that are relatively sparse in the sense that the median count of monitored time series values is zero. Research goals are to understand… read more -
Evaluation of Spatial Estimation Methods for Cluster Detection
Content Type: Abstract
CDC’s BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of… read more -
Localized Cluster Detection Applied to Joint and Separate Military and Veteran Subpopulations
Content Type: Abstract
The Joint VA/DoD BioSurveillance System for Emerging Biological Threats project seeks to improve situational awareness of the health of VA/DoD populations by combining their respective data. Each system uses a version of the Electronic Surveillance… read more