Displaying results 1 - 8 of 20
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Can Chief Complaints Identify Patients with Febrile Syndromes?
Content Type: Abstract
Syndromic surveillance systems often classify patients into syndromic categories based on emergency department (ED) chief complaints. There exists no standard set of syndromes for syndromic surveillance, and the available syndromic case… read more -
Chief Complaint Preprocessing Evaluated on Statistical and Non-Statistical Classifiers
Content Type: Abstract
To determine whether preprocessing chief complaints before automatically classifying them into syndromic categories improves classification performance. -
Consultative Meeting on Chief Complaint Classifiers and Standardized Syndromic Definitions
Content Type: Abstract
We will convene a consultative meeting on chief complaint classifiers and standardized syndromic definitions in Pittsburgh, PA, from September 24-25, -
A Comparison of Chief Complaints and Emergency Department Reports for Identifying Patients with Acute Lower Respiratory Syndrome
Content Type: Abstract
Automated syndromic surveillance systems often classify patients into syndromic categories based on free-text chief complaints. Chief complaints (CC) demonstrate low to moderate sensitivity in identifying syndromic cases. Emergency Department (ED)… read more -
An ISDS-Based Initiative for Conventions for Biosurveillance Data Analysis Methods
Content Type: Abstract
Twelve years into the 21st century, after publication of hundreds of articles and establishment of numerous biosurveillance systems worldwide, there is no agreement among the disease surveillance community on most effective technical methods for… read more -
Evaluation of Preprocessing Techniques for Chief Complaint Classification
Content Type: Abstract
The Real-time Outbreak and Disease Surveillance system collects chief complaints as free text and uses a naïve Bayesian classifier called CoCo to classify the complaints into syndromic categories. CoCo 3.0 has been trained on 28,990 manually clas-… read more -
Identifying Contextual Features to Improve the Performance of an Influenza-Like Illness Text Classifier
Content Type: Abstract
To understand the types of false positive cases identified by an Influenza-like illness (ILI) text classifier by measuring the prevalence of ILI-related concepts that are negated, hypothetical, include explicit mention of temporality, experienced by… read more -
Identifying Respiratory-Related Clinical Conditions from ED Reports with Topaz
Content Type: Abstract
Case detection from chief complaints suffers from low to moderate sensitivity. Emergency Department (ED) reports contain detailed clinical information that could improve case detection ability and enhance outbreak… read more