Best Practice & Research Clinical Anaesthesiology
Volume 23, Issue 1 , Pages 127-143, March 2009

Machine learning techniques to examine large patient databases

  • Geert Meyfroidt (Deputy Head of Clinics)

      Affiliations

    • Department of Intensive Care Medicine, UZ Leuven - Campus Gasthuisberg, Catholic University of Leuven, Herestraat 49, 3000 Leuven, Belgium
    • Corresponding Author InformationCorresponding author. Tel.: +32 16 34 40 21; Fax: +32 16 34 40 15.
  • ,
  • Fabian Güiza (PhD student)

      Affiliations

    • Department of Computer Sciences, Faculty of Engineering, Catholic University of Leuven, Leuven, Belgium
  • ,
  • Jan Ramon (Postdoctoral Researcher)

      Affiliations

    • Department of Computer Sciences, Faculty of Engineering, Catholic University of Leuven, Leuven, Belgium
  • ,
  • Maurice Bruynooghe (Professor, Head of Research Group Declarative Languages and Artificial Intelligence)

      Affiliations

    • Department of Computer Sciences, Faculty of Engineering, Catholic University of Leuven, Leuven, Belgium

To access this article, please choose from the options below

Login to an existing account or Register a new account.

  • Purchase this article for 31.50 USD (You must login/register to purchase this article)

    Online access for 24 hours. The PDF version can be downloaded as your permanent record.

  • Subscribe to this title

    Get unlimited online access to this article and all other articles in this title 24/7 for one year.

  • Claim access now

    For current subscribers with Society Membership or Account Number.

  • Visit SciVerse ScienceDirect to see if you have access via your institution.

PII: S1521-6896(08)00083-9

doi:10.1016/j.bpa.2008.09.003

Best Practice & Research Clinical Anaesthesiology
Volume 23, Issue 1 , Pages 127-143, March 2009