Peterkova A., Michalconok G., Bohm A.
In this paper a classification model is proposed to predict a future state of patient’s cardiac diagnosis based on a large amount of medical data. The methodology of building a prediction model can be applied also to the other areas, such as industrial processes. In our research, we focus on cardiologic datasets of selected patients who were indicated for the ischemic heart disease. The selected sample of patients is divided into four stages of clinical diagnosis. Some of the parameters have a significant impact on the probability of the occurrence of the myocardial infraction. For building a classification model to predict categorical class output was used STATISTICA 13 software.