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The Analysis of Head Injury Data Using Decision Tree Techniques

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Artificial Intelligence in Medicine (AIMDM 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1620))

Abstract

Predicting the outcome of seriously ill patients is a challenging problem for clinicians. One alternative to clinical trials is to analyse existing patient data in an attempt to predict the several outcomes, and to suggest therapies. In this paper we use decision tree techniques to predict the outcome of head injury patients. The work is based on patient data from the Edinburgh Royal Infirmary which contains both background (demographic) data and temporal (physiological) data.

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Author information

Authors and Affiliations

  1. Dept. of Computing Science, University of Aberdeen, Aberdeen, AB24 3UE, Scotland

    A. McQuatt, D. Sleeman & V. Corruble

  2. Dept. of Clinical Neurosciences, Western General Hospital, Edinburgh, Scotland

    P. J. D. Andrews & P. A. Jones

Authors
  1. A. McQuatt
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  2. P. J. D. Andrews
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  3. D. Sleeman
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  4. V. Corruble
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  5. P. A. Jones
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Editor information

Editors and Affiliations

  1. Austrian Research Institute for Artificial Intelligence, Schottengasse 3, A-1010, Vienna, Austria

    Werner Horn

  2. Department of Medicine and Computer Science, Stanford University, 251 Campus Drive, Stanford, CA, 94305-5479, USA

    Yuval Shahar

  3. Department of Medicine Karolinska Institutet, Huddinge University Hospital, Sweden

    Greger Lindberg

  4. Department of Medical Informatics and Image Analysis, Aalborg University, Fredrik Bajers Vej 7D, DK-9000, Aalborg, Denmark

    Steen Andreassen

  5. School of Public Policy, University College London, 29/30 Tavistock Square, London, WC1H 9EZ, UK

    Jeremy Wyatt

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© 1999 Springer-Verlag Berlin Heidelberg

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McQuatt, A., Andrews, P.J.D., Sleeman, D., Corruble, V., Jones, P.A. (1999). The Analysis of Head Injury Data Using Decision Tree Techniques. In: Horn, W., Shahar, Y., Lindberg, G., Andreassen, S., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIMDM 1999. Lecture Notes in Computer Science(), vol 1620. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48720-4_36

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  • DOI: https://doi.org/10.1007/3-540-48720-4_36

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66162-7

  • Online ISBN: 978-3-540-48720-3

  • eBook Packages: Springer Book Archive

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