Intelligent Medical Decision Support System Based on Imperfect Information: The Case of Ovarian Tumor Diagnosis: Studies in Computational Intelligence, cartea 735
Autor Krzysztof Dyczkowskien Limba Engleză Hardback – 11 oct 2017
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Specificații
ISBN-13: 9783319670041
ISBN-10: 3319670042
Pagini: 123
Ilustrații: XXI, 123 p. 55 illus., 51 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.39 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3319670042
Pagini: 123
Ilustrații: XXI, 123 p. 55 illus., 51 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.39 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
Cuprins
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.
Textul de pe ultima copertă
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.
Caracteristici
Describes and outlines the theoretical foundations of the OvaExpert system created by the author and his team Demonstrates how the system helps physicians diagnose ovarian tumors using computational intelligence methods with particular focus on the problem of data incompleteness Introduces basic information on medical diagnosis and the diagnosis of ovarian tumors Discusses original algorithms based on the cardinalities of interval-valued fuzzy sets