Forecasting of Patients Condition in the Monitoring Medical Systems on the Example of Prostate Diseases

Abstract

Goriacha Veronica A., Sokolov Oleksandr Yu., Ugryumova Kateryna M., Antonyan Igor M., Roshin Yuri V., Zelensky Alexandr I., Moshel Fedor G., Nalbandian Taron A. Forecasting of Patients Condition in the Monitoring Medical Systems on the Example of Prostate Diseases. Journal of Education, Health and Sport. 2016;6(5):77-93. eISSN 2391-8306. DOI http://dx.doi.org/10.5281/zenodo.51160

http://ojs.ukw.edu.pl/index.php/johs/article/view/3511

https://pbn.nauka.gov.pl/sedno-webapp/works/725671

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© The Author (s) 2016;

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This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted, non commercial

use, distribution and reproduction in any medium, provided the work is properly cited.

The authors declare that there is no conflict of interests regarding the publication of this paper.

Received: 05.04.2016. Revised 25.04.2016. Accepted: 05.05.2016.

Forecasting of Patients Condition in the Monitoring Medical Systems on the Example of Prostate Diseases

Goriacha Veronica A.¹, Sokolov Oleksandr Yu.², Ugryumova Kateryna M.¹, Antonyan Igor M.³, Roshin Yuri V.³, Zelensky Alexandr I.³, Moshel Fedor G.³, Nalbandian Taron A.³

¹Information technology department, National Aerospace University named by N. Ye. Zhukovsky “Kharkov Aviation Institute”, Ukraine

²Department of Informatics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudzianska 5, 87-100, Torun, Poland

³Department of General and children's oncological urology, Medical Academy of Postgraduate Education Moscow Avenue 195, 61037, Kharkiv, Ukraine

splaijna@gmail.com, osokolov@is.umk.pl, ukatya80@mail.ru, urology.edu.ua@gmail.com

Abstract. The mathematical models and computational methods with implementing them applied information technology of decision support in monitoring medical system are proposed. The method of construction robust monitoring indices based diagnostic models for criteria quality assessment of the systems elements condition is described. The informativeness (significance) assessment method of the systems diagnosing models variables, obtained based on artificial neural networks (ANN) theory instrument is developed. The forecasting method of multivariate time series obtained on the monitoring indices based variables of the dynamic systems condition is developed. The method for solving the condition classification problem of the complex systems elements is improved. The decision support computer system in medical monitoring systems is developed. Application examples of the described methods on diagnosis of medical patients are presented.

Keywords: Decision Support Software System, Reasoning Methods, computational methods, clinical medicine.