New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension
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....
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing,
2018.
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| Edition: | 1st ed. 2018. |
| Series: | SpringerBriefs in Computational Intelligence,
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| Subjects: | |
| ISBN: | 9783319611495 |
| ISSN: | 2625-3704 |
| Online Access: |
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| 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. |
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| Item Description: | Engineering |
| Physical Description: | VIII, 88 p. 48 illus., 47 illus. in color. online resource. |
| ISBN: | 9783319611495 |
| ISSN: | 2625-3704 |