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Objectives: Using chart review as the criterion standard to estimate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of New York State hospital emergency department chief complaint (CC) classifiers for patients < 60 months of age and > 60... Read more

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 diagnosis code and CC are available. A computer program... Read more

Content type: Abstract

Previously we used an “N-Gram” classifier for syndromic surveillance of emergency department (ED) chief complaints (CC) in English for bioterrorism. The classifier is trained on a set of ED visits for which both the ICD diagnosis code and CC are available by measuring the associations of... Read more

Content type: Abstract

Objective: Our objective was to determine how closely the performance of an ngram CC classifier for the gastrointestinal (GI) syndrome matched the performance of the ICD9 classifier.

Content type: Abstract

Objective: Our objective was to compare the performance of the NGram CC classifier to two discrete classifiers based on probabilistic associations with the CC pick list items. Also, we wished to determine the performance of the NGram method applied to CC alone, NN alone, and CC plus NN.

Content type: Abstract

determine the sensitivity, specificity, positive pre-

Content type: Abstract

Effective anomaly detection depends on the timely, asynchronous generation of anomalies from multiple data streams using multiple algorithms. Our objective is to describe the use of a case manager tool for combining anomalies into cases, and for collaborative investigation and disposition of... Read more

Content type: Abstract

In order to detect influenza outbreaks, the New York State (NYS) Department of Health emergency department(ED) syndromic surveillance system uses patients’ chief complaint (CC) to assign visits to respiratory and fever syndromes. Recently, the CDC developed a more specific set of “sub-... Read more

Content type: Abstract

To evaluate four algorithms with varying baseline periods and adjustment for day of week for anomaly detection in syndromic surveillance data.

 

Content type: Abstract

The CDC recently developed sub-syndromes for classifying disease to enhance syndromic surveillance of natural outbreaks and bioterrorism. They have developed ICD9 classifiers for six GI Illness subsyndromes: Abdominal Pain, Nausea and Vomiting (N&V), Diarrhea, Anorexia, Intestinal infections... Read more

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