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Determining Weights of Symptoms in a Diagnostic Inference

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Computer Recognition Systems 2

Part of the book series: Advances in Soft Computing ((AINSC,volume 45))

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Abstract

The paper focuses on modeling weights of symptoms in medical diagnosis. A model of diagnostic inference is proposed in the framework of the Dempster-Shafer theory extended for fuzzy focal elements. The basic probability assignment defined in this theory estimates weights of symptoms. Two such assignments - determined for ‘easy’ diagnostic cases and ‘difficult’ cases, respectively, are calculated for training data, and next combined. Resulting values of the basic probability assigned to focal elements make knowledge about the diagnosis. An algorithm of tuning weights by means of training data is suggested and tested for a medical database from the Internet.

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References

  1. Kacprzyk J, Fedrizzi M (1994) Advances in Dempster-Shafer Theory of Evidence, Wiley, New York.

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Author information

Authors and Affiliations

  1. Institute of Electronics, Silesian University of Technology, 16 Akademicka St, 44-100 Gliwice, Poland

    Ewa Straszecka

Authors
  1. Ewa Straszecka
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Editor information

Editors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzynski , Edward Puchala , Michal Wozniak  & Andrzej Zolnierek , ,  & 

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© 2007 Springer-Verlag Berlin Heidelberg

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Straszecka, E. (2007). Determining Weights of Symptoms in a Diagnostic Inference. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_68

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  • DOI: https://doi.org/10.1007/978-3-540-75175-5_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75174-8

  • Online ISBN: 978-3-540-75175-5

  • eBook Packages: EngineeringEngineering (R0)

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