We have shared a review and a free pdf download link (Google Drive) of Springer’s New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension PDF.
In this book, a new approach for diagnosis and risk evaluation of arterial hypertension is introduced. The new approach was implemented as a hybrid intelligent system combining modular neural networks and fuzzy systems. The different responses of the hybrid system are combined using fuzzy logic.
Finally, two genetic algorithms are used to perform the optimization of the modular neural network 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.
Features of New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension.
- This book is intended to be a reference for scientists and physicians interested in applying soft computing 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.
Table of Contents.
- Fuzzy Logic for Arterial Hypertension Classification.
- Design of a Neuro-Fuzzy System for Diagnosis of Arterial Hypertension.
- Neuro-Fuzzy Modular Approaches for Classification of Arterial Hypertension with a Method for the Expert Rules Optimization.
- Design of Modular Neural Network for Arterial Hypertension Diagnosis.
- Intelligent System for Risk Estimation of Arterial Hypertension.
New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension PDF Download.
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