New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Science & Nature, Technology, Engineering, General Computing
| Author: | Patricia Melin, German Prado-Arechiga | ISBN: | 9783319611495 |
| Publisher: | Springer International Publishing | Publication: | July 4, 2017 |
| Imprint: | Springer | Language: | English |
| Author: | Patricia Melin, German Prado-Arechiga |
| ISBN: | 9783319611495 |
| Publisher: | Springer International Publishing |
| Publication: | July 4, 2017 |
| Imprint: | Springer |
| Language: | English |
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.
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.
