Intelligent Medical Decision Support System Based on Imperfect Information : The Case of Ovarian Tumor Diagnosis

Krzysztof Dyczkowski

ISBN 10: 3319670042 / ISBN 13: 9783319670041

Published by Springer, Berlin, Springer, 2017

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783319670041

Bibliographic Details

• Title: Intelligent Medical Decision Support System Based on Imperfect Information : The Case of Ovarian Tumor Diagnosis
• Publisher: Springer, Berlin, Springer
• Publication Date: 2017
• Language: English
• ISBN 10: 3319670042
• ISBN 13: 9783319670041
• Binding: Buch
• Condition: Neu
• Dimensions: 243W x 171H x 14D millimeters 243 millimeters width by 171 millimeters height by 14 millimeters depth
• Weight: 338 grams

About this title

Synopsis

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.