Cross Disciplinary Consultancy: Negation Detection Use Case

Despite considerable effort since the turn of the century to develop Natural Language Processing (NLP) methods and tools for detecting negated terms in chief complaints, few standardised methods have emerged. Those methods that have emerged (e.g. the NegEx algorithm) are confined to local implementations with customised solutions.

June 18, 2019

Negation Processing in Free Text Emergency Department Data for Public Health Surveillance

Materials associated with the Analytic Solutions for Real-Time Biosurveillance: Negation Processing in Free Text Emergency Department Data for Public Health Surveillance consultancy held January 19-20, 2017 at the University of Utah, Salt Lake City.

Problem Summary

False positive syndrome hits are created when a syndromic classification process cannot properly identify negated terms. For example, a visit is classified into a fever syndrome when the chief complaint or triage note says “denies fever.”

March 23, 2017

Improving Negation Processing in Triage Notes

Emergency Department (ED) triage notes are clinical notes that expand upon the chief complaint, and are included in the AHIC minimum dataset for biosurveillance.1  Clinical notes can improve the accuracy of keyword-based syndromes but require processing that addresses negated terms.2,3  The North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) syndrome classifier searches for keywords in free-text chief complaint and triage note data for the purpose of early event detection.

July 30, 2018

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NSSP Community of Practice

Email: syndromic@cste.org

 

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