New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension

• Κύριοι συγγραφείς: Melin, Patricia (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Prado-Arechiga, German (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: SpringerBriefs in Computational Intelligence,
• Θέματα: Computational intelligence.; Biomedical engineering.; Health informatics.; Computational Intelligence.; Biomedical Engineering and Bioengineering.; Health Informatics.

 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. 

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