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Rough Sets Approach to Medical Diagnosis System

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Advances in Web Intelligence (AWIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3528))

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Abstract

Pawlak’s Rough Sets Theory is one of many mathematical approaches to handle imprecision and uncertainty. The main advantage of the theory over other techniques is that it does not need any preliminary or additional information about analyzed data. This feature of rough set theory favors its usage in decision systems where new relations among data must be uncovered. In this paper we use data from a medical data set containing information about heart diseases and applied drugs to construct a decision system, test its classification accuracy and propose a methodology to improve an accurateness and a testability of generated “if-then” decision rules.

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Author information

Authors and Affiliations

  1. HEITEC AG Systemhaus fuer Automatisierung und Informationstechnologie, Werner-von-Siemens-Strasse 61, 91052, Erlangen, Germany

    Grzegorz Ilczuk

  2. Institut of Informatics, University of Silesia, Bedzinska 39, 41-200, Sosnowiec, Poland

    Alicja Wakulicz-Deja

Authors
  1. Grzegorz Ilczuk
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  2. Alicja Wakulicz-Deja
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Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Piotr S. Szczepaniak

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

  3. Institute of Computer Science, Technical University of Łódź, Poland

    Adam Niewiadomski

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© 2005 Springer-Verlag Berlin Heidelberg

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Ilczuk, G., Wakulicz-Deja, A. (2005). Rough Sets Approach to Medical Diagnosis System. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_32

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  • DOI: https://doi.org/10.1007/11495772_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26219-0

  • Online ISBN: 978-3-540-31900-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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