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North American Fuzzy Information Processing Society Annual Conference

NAFIPS 2017: Fuzzy Logic in Intelligent System Design pp 323–328Cite as

Fuzzy Rule Based Expert System to Diagnose Chronic Kidney Disease

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

Abstract

On time diagnosis of chronic Kidney disease problems is essential because of patient pain and cost of treatment. To alleviate this hazard, in this research a type-1 fuzzy inference system is proposed to diagnosis chronic Kidney disease. The knowledge representation of this system is provided from high level, based on lifestyle of the patient and historical data about his/her problem and some of the clinical examination. We use nine features for diagnosis disease these are age, FBS (Fasting Blood Sugar), Blood urea, Serum creatinine, Na, K, Hemoglobin, rbc (red blood cells), wbc (white blood cells). First we generate type-1 fuzzy inference system then improve our FIS with ANFIS. We generate type-1 fuzzy system for diagnosis chronic kidney disease with real data.

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Author information

Authors and Affiliations

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

    M. H. Fazel Zarandi & Mona Abdolkarimzadeh

Authors
  1. M. H. Fazel Zarandi
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  2. Mona Abdolkarimzadeh
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Corresponding author

Correspondence to M. H. Fazel Zarandi .

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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Zarandi, M.H.F., Abdolkarimzadeh, M. (2018). Fuzzy Rule Based Expert System to Diagnose Chronic Kidney Disease. 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_37

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_37

  • Published:

  • 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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