Procena zdravstvenih rizika korišćenjem Petrijevih mreža

Abstract

Koncept prevencije je sve značajniji u savremenoj medicini. Da bi prevencija bila efektivna i efikasna, neophodno je poznavati zdravstvene faktore rizika određene bolesti kao i kako oni utiču na rizik od oboljevanja. U ovom radu će biti prikazano kako se Petrijeve mreže mogu primeniti u proceni rizika od dobijanja kardiovaskularne bolesti. Osnova za procenu rizika je bila Framinghamska studija, koja se bavi indentifikacijom i prevencijom rizika dobijanja koronarnih bolesti. Koristeći rezultate studije, formulisana je obojena Petrijeva mreža kojom se modeliraju zdravstveni faktori rizika i simulira proces procene rizika da posmatrani pacijent oboli od kardiovaskularne bolesti u budućnosti. Pored procene trenutnog stanja pacijenta, cilj je i da se, promenom različitih vrednosti promenljivih zdravstvenih faktora, simuliraju različiti životni scenariji koji mogu dovesti do smanjenja rizika od oboljevanja. Za modeliranje i simulaciju korišćen je softver CPN Tools.

The concept of prevention is becoming more and more important in modern medicine. In order for prevention to be effective and efficient, is necessary to know the health risk factors of the particular disease and how they can have influence on the disease itself. In this paper it will be shown how Petri nets can be applied in assessing the risk of getting cardiovascular disease. The basis for the assessment of risk was the Framingham heart study, which deals with the identification of and prevention of risk of getting coronary heart disease. Using the results of the study, a colored Petri net has been formulated, which can be used for modeling health risk factors and simulating the process of assessing the risk from getting a cardiovascular disease that a given patient could be suffering in the future. In addition to the assessment of the current condition of the patient, and the aim is that, by changing the values of variables of different health factors, simulate different life scenarios that can lead to a reduction in the risk of disease. For modeling and simulation software CPN Tools has been used.