Displaying results 1 - 8 of 14
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Estimating the incidence of influenza cases that present to emergency departments
Content Type: Abstract
Our laboratory previously established the value of over-the-counter (OTC) sales data for the early detection of disease outbreaks. We found that thermometer sales (TS) increased significantly and early during influenza (flu) season.… read more -
A Method for Detecting and Characterizing Multiple Outbreaks of Infectious Diseases
Content Type: Abstract
We describe an automated system that can detect multiple outbreaks of infectious diseases from emergency department reports. A case detection system obtains data from electronic medical records, extracts features using natural language… 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 -
An Outbreak Detection Algorithm that Efficiently Performs Complete Bayesian Model Averaging Over All Possible Spatial Distributions of Disease
Content Type: Abstract
Many disease-outbreak detection algorithms, such as control chart methods, use frequentist statistical techniques. We describe a Bayesian algorithm that uses data D consisting of current day counts of some event (e.g., 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. -
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 Bayesian Scan Statistic for Spatial Cluster Detection
Content Type: Abstract
This paper develops a new Bayesian method for cluster detection, the ìBayesian spatial scan statistic,î and compares this method to the standard (frequen-tist) scan statistic approach on the task of prospective disease surveillance.