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The Application of Support Diagnose in Mitochondrial Encephalomyopathies

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Rough Sets and Current Trends in Computing (RSCTC 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2475))

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Abstract

The work contains an example of applying the rough sets theory to application of support decision making - diagnose Mitochondrial Encephalomyopathies (MEM) in a child. The resulting decision support system in MEM should maximally limiting the indications for invasive diagnostic methods that finally decide about diagnosis. Moreover he has to shorten the time necessary to making diagnosis. System has arisen using induction (machine learning from examples) - one of the methods artificial intelligence.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, ul. Zeromskiego 3, 41-200, Sosnowiec, Poland

    Piotr Paszek & Alicja Wakulicz-Deja

Authors
  1. Piotr Paszek
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  2. Alicja Wakulicz-Deja
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Editor information

Editors and Affiliations

  1. Penn State Great Valley School of Professional Graduate Studies, 30 East Swedesford Road, Malvern, PA, 19355, USA

    James J. Alpigini

  2. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, R3T 5V6, Canada

    James F. Peters

  3. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

  4. Department of Systems and Information Engineering, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi-City, 371-0816, Japan

    Ning Zhong

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© 2002 Springer-Verlag Berlin Heidelberg

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Paszek, P., Wakulicz-Deja, A. (2002). The Application of Support Diagnose in Mitochondrial Encephalomyopathies. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds) Rough Sets and Current Trends in Computing. RSCTC 2002. Lecture Notes in Computer Science(), vol 2475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45813-1_78

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  • DOI: https://doi.org/10.1007/3-540-45813-1_78

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44274-5

  • Online ISBN: 978-3-540-45813-5

  • eBook Packages: Springer Book Archive

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