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Fuzzy Optimized Classifier for the Diagnosis of Blood Pressure Using Genetic Algorithm

  • Juan Carlos Guzmán
  • Patricia MelinEmail author
  • German Prado-Arechiga
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 749)

Abstract

We propose to optimize the fuzzy rules, which are based on an expert, the objective is to classify the blood pressure level in a correct way with the necessary number of rules and not to have some type of mistake at the moment of giving the diagnosis, since the use of unnecessary rules could cause a confusion in the fuzzy classifier. The fuzzy classifier is only part of the neuro fuzzy hybrid model, which uses techniques such as: neural networks, fuzzy logic and evolutionary computation, in this latter technique, genetic algorithms are used, which use individuals as possible solutions and thus obtain the best solution, in this case find the appropriate number of fuzzy rules for fuzzy system. This study aims to model blood pressure for 24 h and obtain the trend per patient, once this trend is obtained, this information enters a fuzzy system based on rules given by an expert, who will be classified into some of the blood pressure levels based on level European guide and finally give us a diagnosis per patient.

Keywords

Fuzzy system Blood pressure Diagnosis 

Notes

Acknowledgements

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

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Juan Carlos Guzmán
    • 1
  • Patricia Melin
    • 1
    Email author
  • German Prado-Arechiga
    • 2
  1. 1.Tijuana Institute of TechnologyTijuanaMexico
  2. 2.Excel Medical CenterPhiladelphiaUSA

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