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Knowledge discovery and knowledge validation in intensive care

Author

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  • Morik, Katharina
  • Imhoff, Michael
  • Brockhausen, Peter
  • Joachims, Thorsten
  • Gather, Ursula

Abstract

Operational protocols are a valuable means for quality control. However, developing operational protocols is a highly complex and costly task. We present an integrated approach involving both intelligent data analysis and knowledge acquisition from experts that supports the development of operational protocols. The aim is to ensure high quality standards for the protocol through empirical validation during the development, as well as lower development cost through the use of machine learning and statistical techniques. We demonstrate our approach of integrating expert knowledge with data driven techniques based on our effort to develop an operational protocol for the hemodynamic system.

Suggested Citation

  • Morik, Katharina & Imhoff, Michael & Brockhausen, Peter & Joachims, Thorsten & Gather, Ursula, 2000. "Knowledge discovery and knowledge validation in intensive care," Technical Reports 2000,14, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200014
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    References listed on IDEAS

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    1. Guyatt, Gordon & Drummond, Michael & Feeny, David & Tugwell, Peter & Stoddart, Greg & Haynes, R. Brian & Bennett, Kathryn & Labelle, Roberta, 1986. "Guidelines for the clinical and economic evaluation of health care technologies," Social Science & Medicine, Elsevier, vol. 22(4), pages 393-408, January.
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    Cited by:

    1. Fried, Roland & Gather, Ursula & Imhoff, Michael, 2001. "Pattern recognition in intensive care online monitoring," Technical Reports 2001,15, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Marin-Galiano, Marcos & Luebke, Karsten & Christmann, Andreas & Rüping, Stefan, 2005. "Determination of hyper-parameters for kernel based classification and regression," Technical Reports 2005,38, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

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