A Survey of Predicting Heart Disease

M Preethi - Sri Ramakrishna Engineering College, Coimbatore, India
J Selvakumar - Sri Ramakrishna Engineering College, Coimbatore, India

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DOI: http://dx.doi.org/10.30630/joiv.4.2.365


This paper describes various methods of data mining, big data and machine learning models for predicting the heart disease. Data mining and machine learning plays an important role in building an important model for medical system to predict heart disease or cardiovascular disease. Medical experts can help the patients by detecting the cardiovascular disease before occurring. Now-a-days heart disease is one of the most significant causes of fatality. The prediction of heart disease is a critical challenge in the clinical area. But time to time, several techniques are discovered to predict the heart disease in data mining. In this survey paper, many techniques were described for predicting the heart disease.

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Bo Jin ,Chao Che, Zhen Liu, Shulong Zhang, Xiaomeng Yin, And Xiaopeng Wei, “Predicting the Risk of Heart Failure With EHR Sequential Data Modeling” ,IEEE Access 2018.

Aakash Chauhan , Aditya Jain , Purushottam Sharma , Vikas Deep, “Heart Disease Prediction using Evolutionary Rule Learning”, “International Conference on "Computational Intelligence and Communication Technology” (CICT 2018).

Ashir Javeed, Shijie Zhou, Liao Yongjian, Iqbal Qasim, Adeeb Noor, Redhwan Nour4, Samad Wali And Abdul Basit , “An Intelligent Learning System based on Random Search Algorithm and Optimized Random Forest Model for Improved Heart Disease Detection” , IEEE Access 2017.

Senthilkumar Mohan, Chandrasegar Thirumalai, and Gautam Srivastava, “Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques”, IEEE Access 2019.

K.Prasanna Lakshmi, Dr. C.R.K.Reddy, “Fast Rule-Based Heart Disease Prediction using Associative Classification Mining”, IEEE International Conference on Computer, Communication and Control (IC4-2015).

M.Satish, D Sridhar, “Prediction of Heart Disease in Data Mining Technique”, International Journal of Computer Trends & Technology (IJCTT), 2015.

Lokanath Sarangi, Mihir Narayan Mohanty, Srikanta Pattnaik, “An Intelligent Decision Support System for Cardiac Disease Detection”, IJCTA, International Press 2015.

I.S.Jenzi, P.Priyanka, Dr.P.Alli, “A Reliable Classifier Model Using Data Mining Approach for Heart Disease Prediction”, International Journal of Advanced Research in Computer

Science and Software Engineering, 2013.

G. Purusothama and P. Krishnakumari, “A Survey of Data mining techniques on risk prediction: Heart disease”, Indian Journal of Science and Technology, 2015.

Shantakumar B.Patil and Y.S.Kumaraswamy, “Intelligent and Effective Heart Attack Prediction System Using Data Mining and Artificial Neural Network”, European Journal of Scientific Research, Vol.31, No.4, pp.642-656, 2009

Peter, T.J, Somasundaram, K “An empirical study on prediction of heart disease using classification data mining techniques” International Conference on Advances in Engineering, Science and Management (ICAESM) 2012.

Mai Shouman, Tim Turner, Rob Stocker, “ Using data mining techniques in heart disease diagnosis and treatment”, IEEE Japan-Egypt Conference on Electronics, Communications and Computers, 2012.

Syed Umar Amin, Kavita Agarwal, Dr. Rizwan Beg “Genetic Neural Network based Data mining in prediction of Heart disease using risk factors” IEEE Conference on Information and Communication Technologies (ICT 2013).

Shamsher Bahadur Patel, Pramod Kumar Yadav and Dr. D.P.Shukla, “Predict the Diagnosis of Heart Disease Patients using classification Mining Techniques”, IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS), 2013.

Dubey A, Patel R, Choure K, "An efficient data mining and ant colony optimization technique (DMACO) for heart disease prediction", International Journal of Advanced Technology and Engineering Exploration.; 1(1):1-6, 2014.


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JOIV : International Journal on Informatics Visualization
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