Displaying results 425 - 432 of 1300
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Klompas et al. Respond: Automated Public Health Reporting-- Possible with a Coalition of the Willing
Content Type: Abstract
Professor Hripcsak rightly points out some of the challenges inherent in disseminating and sustaining robust information systems to automate the detection and reporting of notifiable diseases using data from electronic medical records (EMR). New… read more -
Laboratory Preparedness for Pandemic Influenza: Estimating the Potential Magnitude of Diagnostic Demand through Trends in Respiratory Illness
Content Type: Abstract
To estimate diagnostic demand in case of pandemic threat using trends in respiratory syndromes (as input for a laboratory preparedness program). -
LAHVA: Linked Animal-Human Health Visual Analytics
Content Type: Abstract
This paper describes our integrated visual analytics framework for analyzing both human emergency room data and veterinary hospital data. -
Late Season Influenza-like Illness in Georgia: Prospective Detection of an Illness Cluster Using Emergency Department Syndromic Surveillance
Content Type: Abstract
This paper describes a cluster of influenza-like illness (ILI) prospectively identified through emergency department (ED) syndromic surveillance (SS). -
Learning Outbreak Regions for Bayesian Spatial Biosurveillance
Content Type: Abstract
This work incorporates model learning into a Bayesian framework for outbreak detection. Our method learns the spatial characteristics of each outbreak type from a small number of labeled training examples, assuming a generative outbreak model with… read more -
Learning Specific Detectors of Adverse Events in Multivariate Time Series
Content Type: Abstract
This paper describes how powerful detectors of adverse events manifested in multivariate series of bio-surveillance data can be learned using only a few labeled instances of such events. -
Learning Stable Multivariate Baseline Models for Outbreak Detection
Content Type: Abstract
We propose a novel technique for building generative models of real-valued multivariate time series data streams. Such models are of considerable utility as baseline simulators in anomaly detection systems. The proposed algorithm, based on Linear… read more -
Lessons Learned from a National Capitol Region Syndromic Surveillance Tabletop Exercise, Spring 2005
Content Type: Abstract
This paper describes lessons learned from a regional tabletop exercise (TTX) of the National Capital Region (NCR) Syndromic Surveillance Network, from the perspective of the Maryland Department of Health and Mental Hygiene (DHMH).