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Interval Type II Fuzzy Rough Set Rule Based Expert System to Diagnose Chronic Kidney Disease

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Fuzzy Information Processing (NAFIPS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 831))

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Abstract

Chronic kidney disease is a worldwide public health problem with an increasing incidence and prevalence, poor outcomes, and high cost. Diagnosis of Chronic Kidney Disease has always been a challenge for physicians. This paper presents an effective method for diagnosis of Chronic Kidney Disease based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-II fuzzy classification, and system evaluation. Fuzzy Rough QuickReduct algorithm feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. Rough set theory is a very useful tool for describing and modeling vagueness in ill-defined environments. In the type-II fuzzy classification step, an “indirect approach” is used for II fuzzy system modeling by implementing the Sugeno index for determining the number of rules in the fuzzy clustering approach. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose Chronic Kidney Disease with an average accuracy of 90%.

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Author information

Authors and Affiliations

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

    Mona Abdolkarimzadeh & M. H. Fazel Zarandi

  2. Tijuana Institute Technology, Tijuana, Mexico

    O. Castillo

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

Correspondence to M. H. Fazel Zarandi .

Editor information

Editors and Affiliations

  1. Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Guilherme A. Barreto

  2. Department of Statistics & Applied Mathematics, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Ricardo Coelho

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Abdolkarimzadeh, M., Fazel Zarandi, M.H., Castillo, O. (2018). Interval Type II Fuzzy Rough Set Rule Based Expert System to Diagnose Chronic Kidney Disease. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_49

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  • DOI: https://doi.org/10.1007/978-3-319-95312-0_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95311-3

  • Online ISBN: 978-3-319-95312-0

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