Prediction of heart disease using learning vector quantization algorithm

In medical field the disease diagnosis is often made based on the knowledge and experience of the medical practitioner. Due to this there are chances of errors, unwanted biases and also takes longer time in accurate diagnosis of disease. In case of heart disease, its diagnosis is most difficult task. It depends on the careful analysis of different clinical and pathological data of the patient by medical experts, which is complicated process. Due to advancement in machine learning, computer and information technology, the researchers and medical practitioners in large extent are interested in the development of automated system for the prediction of heart disease. In this paper we present a prediction system for heart disease using Learning vector Quantization neural network algorithm. The neural network in this system accepts 13 clinical features as input and predicts that there is a presence or absence of heart disease in the patient, along with different performance measures.