Early-Stage Heart attack predication system using Artificial Neural Networks

Abstract

Early prediction of any disease is a matter of concern in today’s highly in a state of complete confusion and disorder lifestyle. Heart related diseases are one of the major causes for death. If we can early predict or identify the heart related diseases, the death rate can be further brought down. Data mining classification technique forms the prediction technique in machine learning. In this paper   analysis   artificial intelligence (AI)is rapidly entering health care and medical examination from automating drudgery and routine tasks in medical practice to managing and avoiding heart attack prediction system. We are utilizing data mining techniques implementing back propagation algorithm analyzing of factors of age sex, chest pain type, cholesterol, blood sugar, electrocardiographic result, heart rate, induced angina and medical resources. As developers create AI systems to take on these tasks, several risks and challenges emerge, including the risk of heart attack to patients from AI system. And more Potential solutions are complex but involve investment in infrastructure for high-quality, representative data; collaborative oversight by both the Food and Drug Administration and other health-care actors; and changes to medical education that will prepare providers for shifting roles in an evolving system.