Hybrid Approach for Heart Disease Detection Using Clustering and ANN

Abstract

Data mining is a process of extracting data from data set and transforming it into understandable structure for further use. Data mining techniques have been applied magnificently in many fields including business, science and bio informatics, and on different types of data like textual, visual, spatial, and real-time and sensor data. Heart disease prediction is treated as most difficult task in the field of medical sciences. Heart disease detection using data mining can answer complicated queries for diagnosing heart disease and thus assist healthcare practitioners to make intelligent clinical decisions which traditional decision support systems cannot. By providing effective treatments, it also helps to reduce treatment costs. The aim of this study is to develop an artificial neural networks-based diagnostic model for heart disease using a complex of traditional and genetic factors of this disease.