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Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications pp 319–327Cite as

A New Model Based on a Fuzzy System for Arterial Hypertension Classification

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 749))

Abstract

In this paper, a method is proposed for classification of the blood pressure of patient (systolic pressure and diastolic pressure). This technique consists on a creating fuzzy system for the classification of the arterial hypertension. The fundamental idea of this paper on achieving Classification of the arterial hypertension of a patient so that the doctor can provide a more accurate Diagnosis, Prevent and control of risk factors that may effect of the patient.

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Acknowledgements

We would like to express our gratitude to the CONACYT, Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, Mexico

    Martha Pulido, Patricia Melin & German Prado-Arechiga

Authors
  1. Martha Pulido
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  2. Patricia Melin
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  3. German Prado-Arechiga
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Corresponding author

Correspondence to Patricia Melin .

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Editors and Affiliations

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

    Oscar Castillo

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

    Patricia Melin

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

    Janusz Kacprzyk

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Pulido, M., Melin, P., Prado-Arechiga, G. (2018). A New Model Based on a Fuzzy System for Arterial Hypertension Classification. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Studies in Computational Intelligence, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-71008-2_24

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  • DOI: https://doi.org/10.1007/978-3-319-71008-2_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71007-5

  • Online ISBN: 978-3-319-71008-2

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