Soft set and Fuzzy Rules enabled SVM Approach for Heart Attack Risk Classification among Adolescents

摘要

Nowadays heart attack is becoming more common among adolescents due to several reasons like heavy work pressure, lack of physical activities, irregular food habits, obesity, eating high fat food, smoking, sedentary life style, heavy drinking and so on. It has been reported that above ten lakh adolescents die every year due to heart related diseases. In literature maximum number of works have been carried out to address heart attack problem among old age people, however there are very less works concentrating on the heart attack detection focusing only adolescents. Hence in this paper the focus is towards adolescents' heart attack risk detection and classification. This is achieved by proposing a novel architecture which detects chances of heart attack in early stages using soft set theory and fuzzy rules. The performance of the proposed architecture is found to be good with respect to several parameters like accuracy, delay and efficiency.