The World Health Organization (WHO) estimated the reason behind 30% of all global deaths corresponds to heart
disease. Heart Disease is one of the main causes of death in India. Many computational techniques were proposed for detection
of heart disease. Hence there is a need to design a diagnosis technology which can help in detection of heart disease. For
detection of heart diseases, Diabetes, cancer Machine learning techniques are widely used. In this research Feature extraction
approach is used to select the important features from the dataset based on the genetic algorithms. For diagnosis of heart disease
ECG signals are used. ECG signal is graphical representation hearts activity. And then classification techniques Support Vector
Machine have been applied on the features to detect heart disease. These machine learning techniques take less time for the
prediction of the disease with accuracy.
