Intelligent Medical Decision Support System Based on Imperfect Information [electronic resource] : The Case of Ovarian Tumor Diagnosis / by Krzysztof Dyczkowski.
Tipo de material: TextoSeries Studies in Computational Intelligence ; 735Editor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XXI, 123 p. 55 illus., 51 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319670058Tema(s): Computational intelligence | Artificial intelligence | Biomedical engineering | Oncology | Computational Intelligence | Artificial Intelligence | Biomedical Engineering/Biotechnology | Oncology | Biomedical Engineering and BioengineeringFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | 1 | No para préstamo |
Acceso multiusuario
Introduction -- Medical foundations -- Elements of fuzzy set theory -- Cardinalities of interval-valued fuzzy sets and their applications in decision making with imperfect information -- OvaExpert System -- Summary.
This book discusses computer-supported medical diagnosis with a particular focus on ovarian tumor diagnosis - since ovarian cancer is difficult to diagnose and has high mortality rates, especially in Central and Eastern Europe. It presents the theoretical foundations (both medical and mathematical) of the intelligent OvaExpert system, which supports decision-making in tumor diagnosis. OvaExpert was created primarily to help gynecologists predict the malignancy of ovarian tumors by applying the existing diagnostic models and using modern methods of computational intelligence that accommodate imprecise and imperfect medical data, both of which are common features of everyday medical practice. The book presents novel methods based on interval-valued fuzzy sets and the theory of their cardinalities.
UABC ; Temporal ; 01/01/2021-12/31/2023.