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International Symposium on Business Modeling and Software Design

BMSD 2018: Business Modeling and Software Design pp 249–259Cite as

Uncover and Assess Rule Adherence Based on Decisions

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 319))

Abstract

Context: Decisions taken by medical practitioners may be based on explicit and implicit rules. By uncovering these rules, a medical practitioner may have the possibility to explain its decisions in a better way, both to itself and to the person which the decision is affecting.

Objective: We investigate if it is possible for a machine learning pipe-line to uncover rules used by medical practitioners, when they decide if a patient could be operated or not. The uncovered rules should have a linguistic meaning.

Method: We are evaluating two different algorithms, one of them is developed by us and named “The membership detection algorithm”. The evaluation is done with the help of real-world data provided by a hospital.

Results: The membership detection algorithm has significantly better relevance measure, compared to the second algorithm.

Conclusion: A machine learning pipe-line, based on our algorithm, makes it possibility to give the medical practitioners an understanding, or to question, how decisions have been taken. With the help of the uncovered fuzzy decision algorithm it is possible to test suggested changes to the feature limits.

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Notes

  1. 1.

    C-reactive protein (CRP) is an annular (ring-shaped), pentameric protein found in blood plasma, whose levels rise in response to inflammation [15].

  2. 2.

    The membership detection algorithm showed better measures than using the rule values stated by a medical practitioner.

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Author information

Authors and Affiliations

  1. Software Engineering Research Lab Sweden, Blekinge Institute of Technology, Karlskrona, Sweden

    Johan Silvander & Mikael Svahnberg

Authors
  1. Johan Silvander
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  2. Mikael Svahnberg
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Corresponding author

Correspondence to Johan Silvander .

Editor information

Editors and Affiliations

  1. Bulgarian Academy of Sciences, Institute of Mathematics and Informatics (IMI)/Interdisciplinary Institute for Collaboration and Research on Enterprise Systems and Technology (IICREST), Sofia, Bulgaria

    Boris Shishkov

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Silvander, J., Svahnberg, M. (2018). Uncover and Assess Rule Adherence Based on Decisions. In: Shishkov, B. (eds) Business Modeling and Software Design. BMSD 2018. Lecture Notes in Business Information Processing, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-319-94214-8_16

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  • DOI: https://doi.org/10.1007/978-3-319-94214-8_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94213-1

  • Online ISBN: 978-3-319-94214-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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