Intelligent Medical Decision Support System Based on Imperfect Information
The Case of Ovarian Tumor Diagnosis
Nonfiction, Health & Well Being, Medical, Allied Health Services, Medical Technology, Computers, Advanced Computing, Artificial Intelligence, General Computing
| Author: | Krzysztof Dyczkowski | ISBN: | 9783319670058 |
| Publisher: | Springer International Publishing | Publication: | October 1, 2017 |
| Imprint: | Springer | Language: | English |
| Author: | Krzysztof Dyczkowski |
| ISBN: | 9783319670058 |
| Publisher: | Springer International Publishing |
| Publication: | October 1, 2017 |
| Imprint: | Springer |
| Language: | English |
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.
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.
