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, -
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 -
SyCo: A Probabilistic Machine Learning Method for Classifying Chief Complaints into Symptom and Syndrome Categories
Content Type: Abstract
Scientists have utilized many chief complaint (CC) classification techniques in biosurveillance including keyword search, weighted keyword search, and naïve Bayes. These techniques may utilize CC-to-syndrome or CC-… read more -
Modeling Clinician Detection Time of a Disease Outbreak Due to Inhalational Anthrax
Content Type: Abstract
We developed a probabilistic model of how clinicians are expected to detect a disease outbreak due to an outdoor release of anthrax spores, when the clinicians only have access to traditional clinical information (e.g., no computer-based alerts). We… read more -
Monitoring Febrile Syndromes from Chief Complaints: Is the Information There?
Content Type: Abstract
There exists no standard set of syndromes for syndromic surveillance, and available syndromic case definitions demonstrate substantial heterogeneity of findings constituting the definition. Many syndromic case definitions require… read more