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Displaying results 1 - 8 of 9
  • 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
    … The classifier is developed from a set of ED visits for which both the ICD diagnosis code and CC are … or “out” of the syndrome. It is possible to dichotomize visits “in” or “out” using N-grams by choosing a cut-off …
  • 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
    … applies the ICD9 classifier to a training set of ED visits for which both the CC and ICD9 code are known. A … Specificity “HEST” (.84) “COUG” (.93) “FEVE” (.47) y Advances in Disease Surveillance 2007;2:1 … A number of …
  • 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
    … Syndromic surveillance of emergency department (ED) visit data is often based on computer algorithms which … applies the ICD9 classifier to a training set of ED visits for which both the CC and ICD9 code are known. A … ly C ou nt s ICD ngram Fig. 2 Daily Counts N gram vs ICD y = 0.56x + 23.68 R = 0.9 0.0 20.0 40.0 60.0 80.0 100.0 …
  • Content Type: Abstract

      Syndromic surveillance of emergency department(ED) visit data is often based on computerized classifiers which assign patient chief complaints (CC) tosyndromes. These classifiers may need to be updatedperiodically to account for changes… read more
    …   Syndromic surveillance of emergency department(ED) visit data is often based on computerized classifiers which … chief complaints (CC) tosyndromes. These classifiers may need to be updatedperiodically to account for changes … automatically based on a training set of patient visits for which both the CC and ICD9 are available. This …
  • 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
    … Syndromic surveillance of emergency department (ED) visit data is often based on computer algorithms which … The classifier is developed from a set of ED visits for which both the ICD diagnosis code and CC are … The classifier is developed from a set of ED visits for which both the ICD diagnosis code and CC are …
  • 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
    … bioterrorism. The classifier is trained on a set of ED visits for which both the ICD diagnosis code and CC are … bioterrorism. The classifier is trained on a set of ED visits for which both the ICD diagnosis code and CC are … CC classifier versus RESP ICD10 Grouping (Test Set) y = 0.642x + 3.0498 R = 0.88 0 5 10 15 20 25 30 35 0 5 10 15 …
  • 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… read more
    … of New Jersey include some 4.2 million records for ED visits to 24 hospitals in the New Jersey and New York, for … the meningitis scare, the “Clinton” chest pain effect, ED visits related to possible anthrax exposure around October … management system. The use of the case manager for ED visits and ELR supports our operational experience of data …
  • Content Type: Abstract

    Ideal anomaly detection algorithms shoulddetect both sudden and gradual changes, while keeping the background false positive alert rate at a tolerable level. The algorithms should also be easy to use. Our objective was to develop an anomaly… read more
    … C2 or C3 alert. The test data were time series of daily visits from two emergency departments (ED) for two … with the usual 2.0 cut-off for two EDs. ORIGINAL GI DAILY VISITS, ~19 MONTHS, ED1 GI 4-DAY OUTBREAKS ROC COMPARISON …