creators_name: Ferguson, Darrell
creators_name: Vinson, Norman G.
creators_name: Morin, Jason
creators_name: Martin, Joel
creators_name: McClinton, Susan
creators_name: Davies, Richard
creators_id: darrell.ferguson@nrc-cnrc.gc.ca
creators_id: norm.vinson@acm.org
creators_id: jasonmorin@jasonmorin.com
creators_id: joel.martin@nrc-cnrc.gc.ca
creators_id: smcclinton@ottawaheart.ca
creators_id: rfdavies@ottawaheart.ca
type: confpaper
datestamp: 2010-10-18 11:05:41
lastmod: 2011-03-11 08:57:36
metadata_visibility: show
title: Identifying ILI Cases from Chief Complaints: Comparing the Accuracy of Keyword and Support Vector Machine Methods
ispublished: pub
subjects: comp-sci-art-intel
subjects: comp-sci-mach-learn
full_text_status: public
keywords: text mining, keywords, support vector machine, syndromic surveillance
note: conversation w/ editor regarding original rejection. Editor says resubmit.

On Wed, 21 Jul 2010, norm.vinson@gmail.com wrote:

    Isn't text mining and machine learning part of AI; isn't AI cog science ?
    Please explain how machine learning is not part of cognitive science.


Yes it is. Please go ahead and re-deposit.

Apologies,

SH
abstract: We compared the accuracy of two methods of identifying ILI cases from chief complaints. We found that a support vector machine method was more accurate than a keyword method.
date: 2009-12
date_type: published
refereed: TRUE
referencetext: 1] Buehler, J.W.; Sonricker, A.; Paladini, M.; Soper, M. & Mostashari,  F. Syndromic Surveillance Practice in the United States: Findings from a Survey of State, Territorial, and Selected Local Health Departments. Advances in Disease Surveillance, 2008; 6(3)
[2] Ontario Ministry of Health and Long-Term Care.    Guidance for Management of Patients with Influenza-like Illness (ILI) in Ambulatory Settings. Province of Ontario, 2009. 
[3] Dara, J.; Dowling, J.N.; Travers, D.; Cooper, G.F.; Chapman, W.W. Chief Complaint Preprocessing Evaluated on Statistical and Non-Statistical Classifiers. Advances in Disease Surveillance 2007; 2:4.
[4] de Bruijn, B.; Cranney, A.; O’Donnell, S.; Martin, J.D.; Forster, A.J. Identifying Wrist Fracture Patients with High Accuracy by Automatic Categorization of X-ray Reports, Journal of the American Medical Informatics Association, 2006, 13(6), 696-698.
 [5] Chapman, W.W. & Dowling, J.N. Can Chief Complaints Identify Patients with Febrile Syndromes? Advances in Disease Surveillance, 2007, 3(6)

citation:   Ferguson, Darrell and Vinson, Norman G. and Morin, Jason and Martin, Joel and McClinton, Susan and Davies, Richard  (2009) Identifying ILI Cases from Chief Complaints: Comparing the Accuracy of Keyword and Support Vector Machine Methods.  [Conference Paper]     
document_url: http://cogprints.org/6837/1/ferguson_et_al__2009_isds.pdf