{"text_format":"5","workbook":"xls","n_sheets":1,"sheets":["report2"],"props":{"last_modified_by":"sharecat"},"not_rendered":{"external_links":1,"defined_names":1},"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":21,"n_cols":5,"rows_kept":21,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[15,2,15,3],[16,2,16,3],[19,2,19,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910299900703321"]
[null,null,"Autore",null,"Melin Patricia"]
[null,null,"Titolo",null,"New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension [[electronic resource] /] / by Patricia Melin, German Prado-Arechiga"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018"]
[null,null,"ISBN",null,"3-319-61149-6"]
[null,null,"Edizione",null,"[1st ed. 2018.]"]
[null,null,"Descrizione fisica",null,"1 online resource (88 pages) : illustrations, tables"]
[null,null,"Collana",null,"SpringerBriefs in Computational Intelligence, , 2625-3704"]
[null,null,"Disciplina",null,"616.132075"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Biomedical engineering"]
[{"$nulls":4},"Health informatics"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Biomedical Engineering and Bioengineering"]
[{"$nulls":4},"Health Informatics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[{"$nulls":3},"Livello bibliografico","Monografia"]
[{"$nulls":3},"Nota di bibliografia","Includes bibliographical references at the end of each chapters and index."]
[null,null,"Nota di contenuto",null,"From the Content: Introduction -- Fuzzy Logic for Arterial Hypertension Classification -- Design of a Neuro Design of a Neuro Design of Arterial Hypertension."]
[{"$nulls":3},"Sommario/riassunto","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."]