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
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.