Deakin University
Browse

Assessing the performance of American chief complaint classifiers on Victorian syndromic surveillance data

conference contribution
posted on 2015-01-01, 00:00 authored by Bahadorreza OfoghiBahadorreza Ofoghi, K Verspoor
Syndromic surveillance systems aim to support early detection of salient disease outbreaks, and to shed timely light on the size and spread of pandemic outbreaks. They can also be used more generally to monitor disease trends and provide reassurance that an outbreak has not occurred. One commonly used technique for syndromic surveillance is concerned with classifying Emergency Department data, such as chief complaints or triage notes, into a set of pre-defined syndromic groups. This paper reports our findings on the investigation of the utility and e↵ectiveness of two existing North American methods for free-text chief complaint classification on a large data set of Australian Emergency Department triage notes, collected from two hospitals in the state of Victoria. To our knowledge, these methods have never before been analysed and compared against each other for their applicability and e↵ectiveness on free text chief complaint classification at this scale or in the Australian context.

History

Pagination

1-6

Location

Sydney, N.S.W.

Start date

2015-10-20

End date

2015-10-21

ISSN

1613-0073

Language

eng

Publication classification

E1.1 Full written paper - refereed, E Conference publication

Copyright notice

2015, The Authors

Editor/Contributor(s)

Barbuto K, Schaper L, Verspoor K

Title of proceedings

BigData 2015 : Proceedings of the Scientific Stream at Big Data in Health Analytics 2015

Event

Health Informatics Society of Australia. Conference (2015 : Sydney, N.S.W.)

Publisher

M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen

Place of publication

Aachen, Germany

Series

Health Informatics Society of Australia Conference

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC