Displaying results 1 - 8 of 13
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A Bayesian Algorithm for Detecting CDC Category A Outbreak Diseases from Emergency Department Chief Complaints
Content Type: Abstract
This paper describes a Bayesian algorithm for diagnosing the CDC Category A diseases, namely, anthrax, smallpox, tularemia, botulism and hemorrhagic fever, using emergency department chief complaints. The algorithm was evaluated on real data and on… read more -
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 -
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, -
An automated influenza-like-illness reporting system using freetext emergency department reports
Content Type: Abstract
Current methods for influenza surveillance include laboratory confirmed case reporting, sentinel physician reporting of Influenza-Like-Illness (ILI) and chief-complaint monitoring from emergency departments (EDs). The current… read more -
Developing an application ontology for mining clinical reports: the extended syndromic surveillance ontology
Content Type: Abstract
Ontologies representing knowledge from the public health and surveillance domains currently exist. However, they focus on infectious diseases (infectious disease ontology), reportable diseases (PHSkbFretired) and internet surveillance… read more -
Building an automated Bayesian case detection system
Content Type: Abstract
Current practices of automated case detection fall into the extremes of diagnostic accuracy and timeliness. In regards to diagnostic accuracy, electronic laboratory reporting (ELR) is at one extreme and syndromic surveillance is at… read more -
Challenges in adapting an natural language processing system for real-time surveillance
Content Type: Abstract
We are developing a Bayesian surveillance system for realtime surveillance and characterization of outbreaks that incorporates a variety of data elements, including free-text clinical reports. An existing natural language processing (… read more