Displaying results 17 - 24 of 75
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Refinement of a Population-Based Bayesian Network for Fusion of Health Surveillance Data
Content Type: Abstract
The ESSENCE demonstration module was built to help DoD health monitors make routine decisions based on disparate evidence sources such as daily counts of ILI-related chief complaints, ratios of positive lab tests for influenza, patient age… read more -
Use of Syndromic Data to Determine Oral Health Visit Burden on Emergency Departments
Content Type: Abstract
Concern over oral health-related ED visits stems from the increasing number of unemployed and uninsured, the cost burden of these visits, and the unavailability of indicated dental care in EDs [1]. Of particular interest to NC state public health… read more -
A Value-Driven Framework For The Evaluation Of Biosurveillance Systems
Content Type: Abstract
Evaluation and strengthening of biosurveillance systems is acomplex process that involves sequential decision steps, numerous stakeholders, and requires accommodating multiple and conflicting objectives. Biosurveillance evaluation, the initiating… 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 -
Hybrid Probabilistic Modeling and Automated Data Fusion for Biosurveillance Applications
Content Type: Abstract
The increased threat of bioterrorism and naturally occurring diseases, such as pandemic influenza, continually forces public health authorities to review methods for evaluating data and reports. The objective of bio-surveillance is to automatically… read more