Displaying results 337 - 344 of 1294
-
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). -
Looking for Anthrax: Feasibility Study of Free Text Analytics for Emergency Department Syndromic Surveillance
Content Type: Abstract
The primary objective of this study is to assess the capability of an advanced text analytics tool that uses natural language processing techniques to extract important medical information collected as part of routine emergency room care (history,… read more -
Mapping Bioterrorism Agents Research Literature
Content Type: Abstract
This paper describes a research effort to map the literature of bioterrorism agents research worldwide using bibliographic analysis, content map analysis, and co-authorship analysis based on Medline data. The objectives of our research are to (a)… read more -
Maximum Entropy Models in Chief Complaint Classification
Content Type: Abstract
This paper describes a novel approach to the statistical classification of free-text chief complaints for the purpose of syndromic surveillance. -
Mental Health Emergency Department Visits in Houston: Developing a Post-Disaster Mental Health Surveillance System
Content Type: Abstract
The objective of this project was to classify and extract mental health emergency department (ED) visits from the Houston Real-time Outbreak and Disease Surveillance (RODS) system. In addition, this project will offer a -
Minimizing False Alarms in Syndromic Surveillance
Content Type: Abstract
This paper describes a method of avoiding false alerts in automated syndromic surveillance algorithms which monitor the temporal relationship between a particular monitored syndrome (the ìtargetî) in relationship to other reference healthcare data… read more -
Mining Pattern Model of Influenza Surveillance
Content Type: Abstract
This paper presents an investigation using data mining techniques to model patterns of influenza from positive case demographics, symptoms and laboratory tests.