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Application of Rough Sets Theory to the Sequential Diagnosis

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Biological and Medical Data Analysis (ISBMDA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4345))

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Abstract

Sequential classification task is typical in medical diagnosis, when the investigations of the patient’s state are repeated several times. Such situation takes place in controlling of the drug therapy efficacy. In this paper the methods of sequential classification using rough sets theory are developed and evaluated. The proposed algorithms, using the set of learning sequences, calculate the lower and upper approximations of the set of proper decision formulas and then use them to make final decision. Depending on the input data different algorithms are derived. Next, all presented algorithms were practically applied in computer-aided recognition of the human acid-base state balance and the results of comparative experimental analysis of in respect of classification accuracy are also presented and discussed.

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Author information

Authors and Affiliations

  1. Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Andrzej Zolnierek

Authors
  1. Andrzej Zolnierek
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Editor information

Editors and Affiliations

  1. The Medical School, Lab of Medical Informatics, Aristotle University, Box 323, 54124, Thessaloniki, Greece

    Nicos Maglaveras  & Ioanna Chouvarda  & 

  2. Laboratory of Medical Informatics, Faculty of Medicine, Aristotle University of Thessaloniki, P.O.Box 323, 54124, Thessaloniki, Greece

    Vassilis Koutkias

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

    Rüdiger Brause

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© 2006 Springer-Verlag Berlin Heidelberg

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Zolnierek, A. (2006). Application of Rough Sets Theory to the Sequential Diagnosis. In: Maglaveras, N., Chouvarda, I., Koutkias, V., Brause, R. (eds) Biological and Medical Data Analysis. ISBMDA 2006. Lecture Notes in Computer Science(), vol 4345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11946465_37

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  • DOI: https://doi.org/10.1007/11946465_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68063-5

  • Online ISBN: 978-3-540-68065-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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