Displaying results 129 - 136 of 199
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Sensitivity and Specificity of an Ngram Method for Classifying Emergency Department Visits into the Respiratory Syndrome in the Turkish Language
Content Type: Abstract
Previously we developed an “Ngram” classifier for syndromic surveillance of emergency department (ED) chief complaints (CC) in Turkish for bioterrorism. The classifier is developed from a set of ED visits for which both the ICD… read more… AT&T Labs applied to the first 10 months of data as a training set to create a Turkish CC RESP classifier. We next … -
Cysticercosis associated epilepsy prevention and control
Content Type: Case Study
Cysticercosis is a frequent health problem in developing countries. The disease is due to infection by Taenia solium larvae and is predominant in areas where pigs and humans cohabite. Inappropriate breeding conditions and poor hygiene especially… read more… ___ Cross-Agency Communication and Collaboration __x_ Training and Resources ___x Technologies and Methodologies … -
Implementation of a Syndromic Surveillance System Using a General Practitioner's House Calls Network
Content Type: Abstract
Recent health events in France, such as the dramatic excess of mortality occurred during the 2003 heat wave showed the need for a better provision of information to health authorities. A new syndromic surveillance system based on the… read more… (Cire),Bordeaux, France (2) French Field Epidemiology Training Programme (PROFET), InVS, ENSP, France (3) SOS … -
Making the Best Use of Textual ED Data for Syndromic Surveillance
Content Type: Webinar
In this webinar Dr. Travers will review two tools developed at the University of North Carolina at Chapel Hill, which aid in processing textual CC’s and triage notes in support of syndromic surveillance. Textual data from emergency departments… read more… Haas, Waller, Schwartz, Mostafa Machine Learning • Train system to identify patterns • Requires gold standard training set • Syndromic surveillance- gold standard • … -
Digital Epidemiology: designing machine learning approaches to combine Internet-based data sources to monitor and forecast disease activity in multiple locations and spatial resolutions
Content Type: Webinar
Presented May 24, 2018. Mauricio Santillana, MS, PhD describes machine learning methodologies that leverage Internet-based information from search engines, twitter microblogs, crowd-sourced disease surveillance systems, electronic… read more… (Massachusetts and Boston) Highlights: (a) dynamic-moving training window, (b) automatic feature selection, (c) … Jon Bickel, and Ben Reis Split data for modeling Training/Fitting Testing In collaboration with: Sam Tideman, … -
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).… cross-jurisdictional alerting protocol; more extensive training of those who monitor ESSENCE, such as alerting to … -
Evaluation of a Syndromic Surveillance System Based on General Practitioner's Data, SOS Medecins Bordeaux
Content Type: Abstract
To describe and evaluate the SOS Medecins Bordeaux syndromic surveillance system .… Aquitaine, Bordeaux, France, 2French Field Epidemiology Training Programme; French Institute for Public Health … -
Preliminary Findings from the BioSense Evaluation Project
Content Type: Abstract
In October 2006, the Centers for Disease Control and Prevention funded four institutions, including Emory University, to conduct evaluations of the BioSense surveillance system. These evaluations include investigations of situations… read more… better public communications capacity, and bene- fits of training in incident command procedures. Interviews for …