Novel Cardiac Risk Factor Stratification Using Neuro-fuzzy Tool

Heart disease continues to be leading cause of morbidity and mortality among adults all over the world. Cardiac risk factor assessment requires a classification system that is robust to the interaction and uncertainty of input factors, as well as being interpretable on the decision made. To meet the requirements, we made use of neuro-fuzzy methods that is a certain novelty in cardiac risk assessment. In this paper two hybrid neuro-fuzzy classifiers, Adaptive Network-based Fuzzy Inference System (ANFIS) and IRIDIA method for neuro-fuzzy identification and data analysis, were applied to determine the cardiac risk factor. These two methods are widely used in the area of decision making. The study demonstrated that the IRIDIA method is efficient in cardiac risk factor assessment.

• Type: Conference
• Year: 2008
• Where: CIMCA
• Authors: Elahe Yargholi, Saman Parvaneh
• Keywords: Cardiac Risk Assessment, Cardiac Risk Factor, CIMCA 2008, Internet Technology, Risk Factor Assessment