Published Paper Details:

Data mining process is discovering knowledge and patterns from extensive collection of data. Hospitals generate a boundless data daily. But, most of Data not used effectively. Use of organized tools for extracting knowledge from clinical databases is not used widely. As per World Health Organization 120 lakh people deaths per year because of heart diseases. Heart disease is a condition, where the heart is incompetent to drive necessary amount of blood to various parts in the body. Precise and timely diagnosis of heart disease is significant for heart failure avoidance and treatment. Traditional Diagnosis of heart disease through clinical findings is not reliable. Machine learning application is reliable and efficient to find healthy people and people with heart disease. The theme of the paper is to use machine learning algorithms to predict heart disease by summarizing the present researches. In this paper the Genetic algorithm and Naive Bayes algorithm is used in the health care dataset to classify the patients if possessing heart diseases or not based on the dataset attributes. .