A Survey on Heart Disease Prediction using Data Mining And Big Data Analytics

T.Nagamani, Dr.S.Logeswari, Dr.B.Gomathy


The World Health Organization (WHO) estimated that cardiovascular diseases (CVD) are the major cause of mortality globally, as well as in India. They are caused by disorders of the heart and blood vessels, and includes coronary heart disease (heart attacks), Data mining plays an important role in building an intelligent prediction model for medical systems to detect heart disease (HD) using data sets of the patients, which helps doctors in reducing the number of mortality rate caused by heart disease. Several studies have been carried out for building model using individually or by combining the data mining techniques namely Classification techniques involving Na´ve bayes (NB), Decision tree (DT), Genetic algorithm (GA), Recurrent Fuzzy neural network (RFNN), Artificial intelligence (AI) and Clustering algorithms like KNN and Support vector machine (SVM). The system can handle complex queries for detection of heart disease and thus help to make intelligent medical decisions. This model would enhance medical care and it can also reduce the costs. This study provides a quick and easy review of understanding the available prediction models using data mining from 2005 to 2017. The comparison shows the accuracy level of each model given by different researchers.

Issue: 10-Special Issue

Year: 2018

Pages: 355-361

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