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Learning of uncertain classification rules in medical diagnosis

  • Contributed Papers
  • Conference paper
  • First Online:
Symbolic and Quantitative Approaches to Uncertainty (ECSQARU 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 548))

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Abstract

In the paper a fuzzy learning algorithm is presented and its application to a real medical problem is detailed.

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References

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Author information

Authors and Affiliations

  1. Istituto di Fisica Cosmica e Tecnologie Relative-C.N.R., Via Ampere 56, 20133, Milano

    Elisabetta Binaghi

Authors
  1. Elisabetta Binaghi
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Editor information

Rudolf Kruse Pierre Siegel

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© 1991 Springer-Verlag Berlin Heidelberg

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Binaghi, E. (1991). Learning of uncertain classification rules in medical diagnosis. In: Kruse, R., Siegel, P. (eds) Symbolic and Quantitative Approaches to Uncertainty. ECSQARU 1991. Lecture Notes in Computer Science, vol 548. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54659-6_75

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  • DOI: https://doi.org/10.1007/3-540-54659-6_75

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54659-7

  • Online ISBN: 978-3-540-46426-6

  • eBook Packages: Springer Book Archive

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