Heart diseases prediction with Data Mining and Neural Network Techniques

Healthiness is the most precise thing in human life. But due to several facts like unhealthy diets, physical inactivity, high blood pressure, smoking habits, etc. health diseases are increasing day by day. Among them heart diseases are the major causes of death. Risk factors like high blood pressure, high blood cholesterol, irregular pulse rate, diabetes, eating habits, age being a major support for occurring heart diseases. Due to the lack of accurate medical support systems which are capable enough to find hidden patterns of medical data and predict diseases, people unable to know the occurrence of diseases in advance. This paper presents a survey about different data mining and neural network classification technologies used in predicting the risk of occurring heart diseases based on risk factors. The risk level of a person is classifying using techniques like K-Nearest Neighbor Algorithm, Decision Trees, Genetic algorithm, Naive Bayes etc. and the accuracy is high when using more attributes and combinations of above techniques.