?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Identifying+ILI+Cases+from+Chief+Complaints%3A+Comparing+the+Accuracy+of+Keyword+and+Support+Vector+Machine+Methods&rft.creator=Ferguson%2C+Darrell&rft.creator=Vinson%2C+Norman+G.&rft.creator=Morin%2C+Jason&rft.creator=Martin%2C+Joel&rft.creator=McClinton%2C+Susan&rft.creator=Davies%2C+Richard&rft.subject=Artificial+Intelligence&rft.subject=Machine+Learning&rft.description=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.&rft.date=2009-12&rft.type=Conference+Paper&rft.type=PeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F6837%2F1%2Fferguson_et_al__2009_isds.pdf&rft.identifier=++Ferguson%2C+Darrell+and+Vinson%2C+Norman+G.+and+Morin%2C+Jason+and+Martin%2C+Joel+and+McClinton%2C+Susan+and+Davies%2C+Richard++(2009)+Identifying+ILI+Cases+from+Chief+Complaints%3A+Comparing+the+Accuracy+of+Keyword+and+Support+Vector+Machine+Methods.++%5BConference+Paper%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F6837%2F