Displaying results 1 - 3 of 3
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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… AT&T Labs). The method applies the ICD9 classifier to a training set of ED visits for which both the CC and ICD9 … visits). We used as our ICD9 classifier an existing ESSENCE filter for the respiratory syndrome, RESP. The ICD9 … -
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… Our objective was to apply the N-Gram method to a training set of Turkish ED data to create a Turkish CC … respiratory grouping of ICD9 codes created by the ESSENCE-CDC project. We then used an N- Gram method adapted … -
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… grouping of ICD10 codes chosen to be similar to the ESSENCE-CDC RESP ICD9 codes. We then used an Ngram method … AT&T Labs applied to the first 10 months of data as a training set to create a Turkish CC RESP classifier. We next …