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. 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.

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

Inhalt

From the Content: Introduction.- Fuzzy Logic for Arterial Hypertension Classification.- Design of a Neuro Design of a Neuro Design of Arterial Hypertension.