Classification Model for Estimation of Risk Factors in Cardiological Diagnostics

The proposed classification model for risk factor estimation makes semi-automatic data analysis based on advanced machine-learning methods. The objective is to provide intelligent computer-based support for medical diagnostics. The developed fuzzy boundary classification determines risk factors importance and adjusts the threshold. Experimental results are presented.