LEADER 03496nam 22006015 450 001 9910299900703321 005 20200706225351.0 010 $a3-319-61149-6 024 7 $a10.1007/978-3-319-61149-5 035 $a(CKB)4340000000062775 035 $a(MiAaPQ)EBC4898802 035 $a(DE-He213)978-3-319-61149-5 035 $z(PPN)258861770 035 $a(PPN)203669940 035 $a(EXLCZ)994340000000062775 100 $a20170704d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aNew Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension$b[electronic resource] /$fby Patricia Melin, German Prado-Arechiga 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (88 pages) $cillustrations, tables 225 1 $aSpringerBriefs in Computational Intelligence,$x2625-3704 311 $a3-319-61148-8 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aFrom the Content: Introduction -- Fuzzy Logic for Arterial Hypertension Classification -- Design of a Neuro Design of a Neuro Design of Arterial Hypertension. 330 $aIn this book, a new approach for diagnosis and risk evaluation of ar-terial hypertension is introduced. The new approach was implement-ed as a hybrid intelligent system combining modular neural net-works and fuzzy systems. The different responses of the hybrid system are combined using fuzzy logic. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters. The experimental results obtained using the proposed method on real pa-tient data show that when the optimization is used, the results can be better than without optimization. This book is intended to be a refer-ence for scientists and physicians interested in applying soft compu-ting techniques, such as neural networks, fuzzy logic and genetic algorithms, in medical diagnosis, but also in general to classification and pattern recognition and similar problems. 410 0$aSpringerBriefs in Computational Intelligence,$x2625-3704 606 $aComputational intelligence 606 $aBiomedical engineering 606 $aHealth informatics 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009 615 0$aComputational intelligence. 615 0$aBiomedical engineering. 615 0$aHealth informatics. 615 14$aComputational Intelligence. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aHealth Informatics. 676 $a616.132075 700 $aMelin$b Patricia$4aut$4http://id.loc.gov/vocabulary/relators/aut$0762263 702 $aPrado-Arechiga$b German$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299900703321 996 $aNew Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension$92501312 997 $aUNINA