Mafia and FP-growth to detect cardiovascular problem

Abstract: In recent years various software tools and various algorithms have been proposed by the researchers for budding successful medical decision support systems. Moreover, better algorithms and better tools are developed and represent day by day. Diagnosing of heart disease is one of the vital concern and many researchers investigated to widen intelligent medical decision support systems to improve the skill of the physicians. Such an automated system for medical diagnosis would perk up medical care and lessen expenditure [Ref 1]. However, perfect diagnosis at before time and appropriate consequent treatment can upshot in momentous life saving. Many authentic world tribulations in various fields such as business, science, industry and medicine can be getting to the bottom of by using classification approach. Neural Networks have emerged as an important tool for classification. The advantages of Neural Networks helps for efficient classification of given data. In cardiology, artificial neural networks have been successfully applied to problems in classification and detection Electrocardiographic. This study mainly focuses on the current status of artificial neural network technology in cardiovascular medical research. Keywords: artificial neural networks, medical diagnosis, cardiovascular, Electrocardiographic