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New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension

  • Book
  • © 2018

Overview

Authors:
  1. Patricia Melin

    1. Division of Graduate Studies, Tijuana Institute of Technology Division of Graduate Studies, Tijuana, Mexico

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  2. German Prado-Arechiga

    1. Cardiodiagnostico, Excel Medical Center Cardiodiagnostico, Tijuana, Mexico

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    You can also search for this author in PubMed   Google Scholar

  • Presents a new approach for diagnosis and risk evaluation of arterial hypertension
  • Demonstrates the implementation of the approach as a hybrid intelligent system combining modular neural networks and fuzzy systems
  • Two genetic algorithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters
  • The experimental results obtained using the proposed method on real patient data show that when the optimization is used, the results can be better than without optimization
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)

Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-viii
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  2. Introduction

    • Patricia Melin, German Prado-Arechiga
    Pages 1-3

  3. Fuzzy Logic for Arterial Hypertension Classification

    • Patricia Melin, German Prado-Arechiga
    Pages 5-13

  4. Design of a Neuro-Fuzzy System for Diagnosis of Arterial Hypertension

    • Patricia Melin, German Prado-Arechiga
    Pages 15-22

  5. Neuro-Fuzzy Modular Approaches for Classification of Arterial Hypertension with a Method for the Expert Rules Optimization

    • Patricia Melin, German Prado-Arechiga
    Pages 23-47

  6. Design of Modular Neural Network for Arterial Hypertension Diagnosis

    • Patricia Melin, German Prado-Arechiga
    Pages 49-62

  7. Intelligent System for Risk Estimation of Arterial Hypertension

    • Patricia Melin, German Prado-Arechiga
    Pages 63-75

  8. Conclusions

    • Patricia Melin, German Prado-Arechiga
    Pages 77-78

  9. Back Matter

    Pages 79-88
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Keywords

About this book

In this book, a new approach for diagnosis and risk evaluation of ar-terial hypertension is introduced. The new approach was implement-ed as a hybrid intelligent system combining modular neural net-works and fuzzy systems. The different responses of the hybrid system are combined using fuzzy logic. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters. The experimental results obtained using the proposed method on real pa-tient data show that when the optimization is used, the results can be better than without optimization. This book is intended to be a refer-ence for scientists and physicians interested in applying soft compu-ting techniques, such as neural networks, fuzzy logic and genetic algorithms, in medical diagnosis, but also in general to classification and pattern recognition and similar problems.

Authors and Affiliations

  • Division of Graduate Studies, Tijuana Institute of Technology Division of Graduate Studies, Tijuana, Mexico

    Patricia Melin

  • Cardiodiagnostico, Excel Medical Center Cardiodiagnostico, Tijuana, Mexico

    German Prado-Arechiga

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