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A Type-2 Fuzzy Expert System for Diagnosis of Leukemia

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Fuzzy Logic in Intelligent System Design (NAFIPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 648))

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Abstract

Medical field, especially in the diagnosis and treatment, is facing with inherent uncertainty. Causes of leukemia can be different factors that determining of them is with uncertainty. Owing to the high potential of the fuzzy expert systems for managing uncertainty associated to the medical diagnosis, in this paper, we propose a type-2 fuzzy expert system for Leukemia diagnosis. In this system, we use Mamdani-style inference that has high interpretability to clarify the results of system to experts. The classification accuracy of the type-2 fuzzy system for Leukemia diagnosis has obtained about 94% which demonstrate its capability for helping experts to early diagnosis of the disease.

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Authors and Affiliations

  1. Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

    Ali Akbar Sadat Asl & Mohammad Hossein Fazel Zarandi

Authors
  1. Ali Akbar Sadat Asl
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  2. Mohammad Hossein Fazel Zarandi
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Corresponding author

Correspondence to Ali Akbar Sadat Asl .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Reformat

  5. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Ontario, Canada

    William Melek

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Sadat Asl, A.A., Zarandi, M.H.F. (2018). A Type-2 Fuzzy Expert System for Diagnosis of Leukemia. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67136-9

  • Online ISBN: 978-3-319-67137-6

  • eBook Packages: EngineeringEngineering (R0)

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