Losеv A.G., Mazеpa E.A., Sulеymanova Kh.M. On Interrelation of Some Signs of RTM Diagnostics of Mammary Glands Diseases

http://dx.doi.org/10.15688/jvolsu1.2015.4.4

Losev Aleksandr Georgievich 
Doctor of Physical and Mathematical Sciences, Professor,
Department of Mathematical Analysis and Function Theory
Volgograd State University
This email address is being protected from spambots. You need JavaScript enabled to view it. , This email address is being protected from spambots. You need JavaScript enabled to view it.
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation


Mazepa Elena Alekseevna 
Candidate of Physical and Mathematical Sciences, Associate Professor,
Department of Mathematical Analysis and Function Theory
Volgograd State University
This email address is being protected from spambots. You need JavaScript enabled to view it. , This email address is being protected from spambots. You need JavaScript enabled to view it.
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

 

Suleymanova Кhedi Movladovna 
Postgraduate Student, Department of Mathematical Analysis and Function Theory,
Volgograd State University
This email address is being protected from spambots. You need JavaScript enabled to view it. , This email address is being protected from spambots. You need JavaScript enabled to view it.
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation
 

Abstract. The article is devoted to the development of mining methods and interpreting medical thermometric data for breast diseases diagnostics. The methods of applied statistics and artificial intelligence are successfully used to solve problems in medical diagnostics, monitoring and forecasting. The problem of medical diagnostics has traditionally developed two classes of systems, and different methods are put into their base. One class consists of systems based on statistical models, and the other one – on mathematical ones. The foundation of the latter is represented by mathematical algorithms involved in the search. There is usually a partial correspondence between the symptoms of another patient and the symptoms previously observed patients, the diagnoses of which are known. The knowledge of experts is at the core systems of the second class. These algorithms operate on the patient information and knowledge on diseases, presented in a form more or less close to the views of doctors (and described by expert physicians), which is achieved due to the implicit or explicit use of ontologies of medical diagnostics.

Key words: microwave radio thermometry, breast screening, correlation analysis, malignant breast tumors.

Creative Commons License
On Interrelation of Some Signs of RTM Diagnostics of Mammary Glands Diseases by Losеv A.G., Mazеpa E.A., Sulеymanova Kh.M. is licensed under a Creative Commons Attribution 4.0 International License.

Citation in EnglishScience Journal of Volgograd State University. Mathematics. Physics. №4 (29) 2015 pp. 35-44

Attachments:
Download this file (Losev_Mozepa_Suleimanova.pdf) Losev_Mazepa_Suleimanova.pdf
URL: https://mp.jvolsu.com/index.php/en/component/attachments/download/460
995 Downloads