Dyczkowski, Krzysztof.
Intelligent Medical Decision Support System Based on Imperfect Information The Case of Ovarian Tumor Diagnosis / [electronic resource] : - 1st ed. 2018. - XXI, 123 p. 55 illus., 51 illus. in color. | Binding - Card Paper | - Studies in Computational Intelligence, 735 1860-949X ; . - Studies in Computational Intelligence, 735 .
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.
9783319670058
Computer Engineering
Artificial Intelligence. Biomedical Engineering/Biotechnology. Oncology. Biomedical Engineering and Bioengineering.
006.3
Intelligent Medical Decision Support System Based on Imperfect Information The Case of Ovarian Tumor Diagnosis / [electronic resource] : - 1st ed. 2018. - XXI, 123 p. 55 illus., 51 illus. in color. | Binding - Card Paper | - Studies in Computational Intelligence, 735 1860-949X ; . - Studies in Computational Intelligence, 735 .
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.
9783319670058
Computer Engineering
Artificial Intelligence. Biomedical Engineering/Biotechnology. Oncology. Biomedical Engineering and Bioengineering.
006.3