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标题：Exploration Risk Factors and Prediction of Heart Disease Using Mining Techniques
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作者：Sowmiya.T ; Dr. V. Sai Shanmuga Raja
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2018
卷号：6
期号：2
页码：971
DOI：10.15680/IJIRCCE.2018.0602053
出版社：S&S Publications
摘要：The main aim is to predict the Heart Diseases based on the parameters, the analysis of high risk factorsof developing heart diseases are identified using Intelligent Support Vector [ISV] Algorithm with rule miningtechniques. The World Health Organization estimates that by 2030 there will be approximately 350 million youngpeople (below 30 to 40 years) with heart diseases associated with renal complications, stroke and peripheral vasculardisease. Heart disease is most common in present era. The treatment cost of heart disease is not affordable by most ofthe patients. So we can reduce this problem by a Heart Disease Prediction System (HDPS). It is helpful for earlierdiagnosis of heart disease. Data mining techniques are used for the construction of HDPS. In health care field somesystems use large healthcare data in varied forms such as images, texts, charts and numbers. Our aim is to analyze therisk factors and system conditions to detect heart disease early. Using effective methods to identify and extract keyinformation that describes aspects of developing a prediction model, sample size and number of events, risk predictorselection. Using the new algorithm called Intelligent Support Vector [ISV], we can easily identify the heart disease withvarious attributes and risk factor specifications. Based on these parameters, the analysis of high risk factors ofdeveloping heart disease is identified using mining principles. Use of data mining algorithms will result in quickprediction of disease with high accuracy.
关键词：Prediction; Heart Disease; HDPS; Random Forest; Naïve Bayes; Health Records