Learning from pathology databases to improve the laboratory diagnosis of infectious diseases

Alice Richardson, Fariba Shadabi, Brett Lidbury

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)

Abstract

This paper investigates the effect of data pre-processing and the use of ensemble on the accuracy of decision trees. The methodology is illustrated using a previously unanalysed data set from ACT Pathology (Canberra, Australia) relating to Hepatitis B and Hepatitis C patients
Original languageEnglish
Title of host publicationE-Health: First IMIA/IFIP Joint Symposium, E-Health 2010: Held as part of WCC 2010: Proceedings
EditorsHiroshi Takeda
Place of PublicationUnited States
PublisherSpringer
Pages226-227
Number of pages2
ISBN (Print)9783642155147
DOIs
Publication statusPublished - 2010
EventInternational E-Health Joint Conference 2010 - Brisbane, Australia
Duration: 20 Sep 201023 Sep 2010

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume335
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

ConferenceInternational E-Health Joint Conference 2010
CountryAustralia
CityBrisbane
Period20/09/1023/09/10

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  • Cite this

    Richardson, A., Shadabi, F., & Lidbury, B. (2010). Learning from pathology databases to improve the laboratory diagnosis of infectious diseases. In H. Takeda (Ed.), E-Health: First IMIA/IFIP Joint Symposium, E-Health 2010: Held as part of WCC 2010: Proceedings (pp. 226-227). (IFIP Advances in Information and Communication Technology; Vol. 335). Springer. https://doi.org/10.1007/978-3-642-15515-4_25