Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Methodologies for Intelligent Systems

ISMIS 1996: Foundations of Intelligent Systems pp 438–447Cite as

The application of rough sets-based data mining technique to differential diagnosis of meningoenchepahlitis

  • Communications Session 5B Learning and Discovery Systems
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1079))

Abstract

The application of rough sets-based data mining tool called KDD-R to the analysis of clinical data is described. The main practical problem tackled with the data mining technique is a differential diagnosis of bacterial versus viral meningoenchephalis. We present the relevant aspects of the variable precision rough sets model underlying the system KDD-R, the basic operational stages of KDD-R, and the results and their clinical interpretation conducted by the domain expert.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Katzberg, J. and Ziarko, W. 1994. Variable Precision Rough Sets with Asymmetric Bounds, In Ziarko, W. (ed.) Rough Sets, Fuzzy Sets and Knowledge Discovery, Springer-Verlag, pp. 167–177.

    Google Scholar 

  • Pawlak, Z. 1991. Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers.

    Google Scholar 

  • Piatetsky-Shapiro, G. (ed.) 1993. Proc. of AAAI-93 Workshop on Knowledge Discovery in Datbases, Washington D.C.

    Google Scholar 

  • Piatetsky-Shapiro, G. and Frawley, W. J. (eds.) 1991. Knowledge Discovery in Databases, AAAI/MIT Press.

    Google Scholar 

  • Ziarko, W. 1993. Variable Precision Rough Set Model. Journal of Computer and System Sciences, Vol. 46, No. 1, pp.39–59.

    Google Scholar 

  • Fayyad, U. and Uthurusamy, R. (eds.) 1995. Proceedings of the First International Conference on Knowledge Discovery and Data Mining, Montreal, Canada 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Medicine Medical Research Institute, Tokyo Medical and Dental University, 1-5-45 Yushima, Bukyo-ku, 113, Tokyo, Japan

    Shusaku Tsumoto

  2. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    Wojciech Ziarko

Authors
  1. Shusaku Tsumoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wojciech Ziarko
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Zbigniew W. Raś Maciek Michalewicz

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tsumoto, S., Ziarko, W. (1996). The application of rough sets-based data mining technique to differential diagnosis of meningoenchepahlitis. In: Raś, Z.W., Michalewicz, M. (eds) Foundations of Intelligent Systems. ISMIS 1996. Lecture Notes in Computer Science, vol 1079. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61286-6_168

Download citation

  • DOI: https://doi.org/10.1007/3-540-61286-6_168

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61286-5

  • Online ISBN: 978-3-540-68440-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation