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ISSN: 2229-6956(ONLINE) DOI: 10.21917/ijsc.2013.0087 ICTACT JOURNAL ON SOFT COMPUTING, JULY 2013, VOLUME: 03, ISSUE: 04 605 REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES R. Chitra 1 and V. Seenivasagam 2 1 Department of Computer Science and Engineering, Noorul Islam Centre for Higher Education, India E-mail: [email protected] 2 Department of Information Technology, National Engineering College, India E-mail: [email protected] Abstract The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper. Keyword: Neural Network, Hybrid Intelligent Algorithm, Heart Disease Prediction, Computer Aided Decision Support System 1. INTRODUCTION Heart Diseases remain the biggest cause of deaths for the last two decades. Recently computer technology and machine learning techniques to develop software to assist doctors in making decision of heart disease in the early stage. The diagnosis of heart disease depends on clinical and pathological data. Heart disease prediction system can assist medical professionals in predicting heart disease status based on the clinical data of patients. In biomedical field data mining plays an essential role for prediction of diseases In biomedical diagnosis, the information provided by the patients may include redundant and interrelated symptoms and signs especially when the patients suffer from more than one type of disease of the same category. The physicians may not able to diagnose it correctly. Data mining with intelligent algorithms can be used to tackle the said problem of prediction in medical dataset involving multiple inputs. Now a day’s Artificial neural network has been used for complex and difficult tasks. The neural network is trained from the historical data with the hope that it will discover hidden dependencies and that it will be able to use them for predicting. Feed forward neural networks trained by back- propagation have become a standard technique for classification and prediction tasks. The healthcare industry collects huge amounts of healthcare data and that need to be mined to discover hidden information for effective decision making. Discover of hidden patterns and relationships often go unexploited [6].
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