Displaying results 1 - 5 of 5
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Talking Turkish: Using N-Grams for Syndromic Surveillance in a Turkish Emergency Department without the Need for English Translation
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… read more -
The NGram CC Classifier: A Novel Method of Automatically Creating CC Classifiers Based on ICD9 Groupings
Content Type: Abstract
Syndromic surveillance of emergency department (ED) visit data is often based on computer algorithms which assign patient chief complaints (CC) to syndromes. ICD9 code data may also be used to develop visit classifiers for syndromic surveillance but… read more -
The Performance of a NGram Classifier for Patients' Chief Complaint Based on a Computerized Pick List Entry and Free Text in an Italian Emergency Department
Content Type: Abstract
Syndromic surveillance of emergency department (ED) visit data is often based on computer algorithms which assign patient chief complaints (CC) and ICD code data to syndromes. The triage nurse note (NN) has also been used for… read more -
Optimizing Performance of an Ngram Method for Classifying Emergency Department Visits into the Respiratory Syndrome
Content Type: Abstract
A number of different methods are currently used to classify patients into syndromic groups based on the patient’s chief complaint (CC). We previously reported results using an “Ngram” text processing program for building classifiers… read more -
Sensitivity and Specificity of an Ngram Method for Classifying Emergency Department Visits into the Respiratory Syndrome in the Turkish Language
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… read more