| Description |
1 online resource (viii, 88 pages) |
| Series |
SpringerBriefs in applied sciences and technology, computational intelligence, 2191-530X |
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SpringerBriefs in applied sciences and technology. Computational intelligence. 2191-530X
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| Contents |
Preface; Contents; 1 Introduction; Abstract; References; 2 Fuzzy Logic for Arterial Hypertension Classification; Abstract; 2.1 Introduction; 2.2 Methodology; 2.2.1 Type of Blood Pressure Diseases; 2.2.2 Risk Factors; 2.2.3 Fuzzy Logic and Hypertension; 2.3 Simulation and Results; 2.4 Design and Development of the Fuzzy Logic System; 2.5 Conclusions; References; 3 Design of a Neuro-Fuzzy System for Diagnosis of Arterial Hypertension; Abstract; 3.1 Introduction; 3.2 Methodology; 3.2.1 Blood Pressure; 3.2.2 Low Blood Pressure (Hypotension); 3.2.3 High Blood Pressure (Hypertension) |
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3.3 Development and Final Design of the Neuro Fuzzy Hybrid Model3.4 Conclusions; References; 4 Neuro-Fuzzy Modular Approaches for Classification of Arterial Hypertension with a Method for the Expert Rules Optimization; Abstract; 4.1 Introduction; 4.2 Problem Statement and Proposed Method; 4.2.1 Blood Pressure; 4.2.2 Type of Blood Pressure Diseases; 4.2.3 Hypotension; 4.2.4 Hypertension; 4.2.5 Risk Factors; 4.2.6 Modular Neural Network Model for Classification of BP; 4.2.7 Design of the Fuzzy Systems for the Classification; 4.2.7.1 Design of the Fuzzy Classifier 1 |
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4.2.7.2 Design of the Fuzzy Classifier 2Design of the Fuzzy Classifier 3; 4.2.8 The Optimization of the Fuzzy System Using a Genetic Algorithm (GA); 4.2.8.1 Design of the Fuzzy Classifier 4 Optimized with GA; 4.3 Simulation Results of the Proposed Method; 4.4 Comparison of Results; 4.5 Conclusion; Acknowledgements; References; 5 Design of Modular Neural Network for Arterial Hypertension Diagnosis; Abstract; 5.1 Introduction; 5.2 Overview of Related Works; 5.3 Neural Networks; 5.4 Arterial Hypertension; 5.5 Pulse Pressure; 5.6 Problem Statement and Proposed Method; 5.7 Simulation Results |
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5.8 ConclusionsAcknowledgements; References; 6 Intelligent System for Risk Estimation of Arterial Hypertension; Abstract; 6.1 Introduction; 6.1.1 Blood Pressure and Hypertension; 6.1.2 Neural Network for a Hypertension Diagnosis; 6.1.3 Fuzzy Logic and Arterial Hypertension; 6.1.4 Fuzzy Logic and Pulse; 6.2 Proposed Method; 6.3 Methodology; 6.3.1 Graphical User Interface; 6.4 Results and Discussion; 6.5 Conclusions and Future Work; Acknowledgements; References; 7 Conclusions; Abstract; Appendix A; Index |
| Summary |
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 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Hypertension -- Diagnosis.
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Hypertension -- Risk assessment
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Neural networks (Computer science)
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Soft computing.
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Fuzzy logic.
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Hypertension -- diagnosis
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Neural Networks, Computer
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Biomedical engineering.
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Medical equipment & techniques.
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Artificial intelligence.
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HEALTH & FITNESS -- Diseases -- General.
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MEDICAL -- Clinical Medicine.
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MEDICAL -- Diseases.
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MEDICAL -- Evidence-Based Medicine.
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MEDICAL -- Internal Medicine.
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Soft computing
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Neural networks (Computer science)
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Hypertension -- Diagnosis
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Fuzzy logic
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Biomedical engineering
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Computational intelligence
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Engineering
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Medical informatics
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| Form |
Electronic book
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| Author |
Prado-Arechiga, German, author
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| ISBN |
9783319611495 |
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3319611496 |
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