Presentation: Development & Testing of an Automated Syndrome Classifier for ED Data

The presentation will include an introduction to NC DETECT, biosurveillance, and information retrieval techniques for data representation and classification, as well as a review of methods for evaluating automated classifiers. The new system, Emergency Medical Text Classifier (EMT-C) will be described, followed by a presentation of the results of pilot EMT-C testing.

When Mar 28, 2012
from 04:00 PM to 05:00 PM
Where Health Sciences Library room 328
Contact Name
Contact Phone 919-962-0182
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Drs. Mostafa and Travers will describe approaches to automated syndrome classification using clinical text, as applied to a new system created to classify emergency department (ED) records that meet criteria for acute infectious disease surveillance (aka biosurveillance). The new system was created as part of an NLM-funded project, “Adapting NLP Tools for Biosurveillance.” The system is currently being evaluated for biosurveillance use by public health officials through the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).

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