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Fuzzy Inference Systems for Multistage Diagnosis of Acute Renal Failure in Children

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Medical Data Analysis (ISMDA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2868))

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Abstract

This paper presents fuzzy inference systems developed for the multistage pattern recognition. Two different methods of generating fuzzy if-then rules from empirical data are presented and their application to the computer-aided diagnosis of acute renal failure are discussed and compared with algorithms based on statistical model.

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References

  1. Kurzynski, M.: Probabilistic Algorithms, Neural Networks, and Fuzzy System Applied to the Multistage Diagnsis of Acute Abdominal Pain, A Comparative Study of Methods. In: Proc. 1st Int. Conference on Fuzzy Systems and Knowledge Discovery, Singapore, November 18-20 (2002) (CD ROM)

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Author information

Authors and Affiliations

  1. Faculty of Electronics, Division of Medical Informatics, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzynski

Authors
  1. Marek Kurzynski
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and applied Computer Sciences, IBaI, Germany

    Petra Perner

  2. Institute of Informatics, Johann Wolfgang Goethe-Universität, 60054, Frankfurt a.M., Germany

    Rüdiger Brause

  3. Institut für Biochemie, Charité, Campus Mitte, Monbijoustr. 2, 10117, Berlin, Germany

    Hermann-Georg Holzhütter

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© 2003 Springer-Verlag Berlin Heidelberg

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Kurzynski, M. (2003). Fuzzy Inference Systems for Multistage Diagnosis of Acute Renal Failure in Children. In: Perner, P., Brause, R., Holzhütter, HG. (eds) Medical Data Analysis. ISMDA 2003. Lecture Notes in Computer Science, vol 2868. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39619-2_13

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  • DOI: https://doi.org/10.1007/978-3-540-39619-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20282-0

  • Online ISBN: 978-3-540-39619-2

  • eBook Packages: Springer Book Archive

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