• V. P. Martsenyuk University of Bielsko-Biala, the Republic of Poland
  • I Ye. Andrushchak Lutsk National Technical University




system analysis, decision support systems, information system, simulation, optimization, dynamic system, qualitative analysis, decision tree, classification rule, health research systems


The work presents our results in field of application of system analysis methods to problem of medical research. We emphasize effects of uncertainty that should be taken into account in such complex processes. Medical system research requires information support system implementing data mining algorithms resulting in decision trees or IF-THEN rules. Besides that such system should be object-oriented and web-integrated.

The aim of this study was to develop information support system based on data mining algorithms applied to system analysis method for medical system research. System analysis methods were used for qualitative analysis of diseases mathematical models. Algorithms such as decision tree induction and sequential covering algorithm were applied for data mining from learning data set.

We observed the complex qualitative behavior of population and diseases models depending on parameters and controllers even without considering probabilistic nature of the most of quantities and parameters of information models.


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How to Cite

Martsenyuk, V. P., & Andrushchak, I. Y. (2017). ON PREDICTION AND DECISION MAKING UNDER UNCERTAINTIES FOR MEDICAL SYSTEMS RESEARCH PROBLEMS. Medical Informatics and Engineering, (4), 12–17. https://doi.org/10.11603/mie.1996-1960.2016.4.7055