Prediction of Heart Diseases in Data Mining Techniques

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-24 Number-1
Year of Publication : 2015
Authors : M.Sathish, D.Sridhar


M.Sathish, D.Sridhar "Prediction of Heart Diseases in Data Mining Techniques". International Journal of Computer Trends and Technology (IJCTT) V24(1):45-49, June 2015. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Data mining technology provides a user- oriented approach to novel and hidden patterns in the data and discovering association rules in medical data to predict heart disease. mapping medical data to a transaction format suitable for mining association rules and identifying useful constraints. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain.

[1] Nitika Dahiya, Madan Lal Yadav, "A Soft Computing Approach for Heart Disease Analysis", International Journal of Computer Trends and Technology (IJCTT) – volume 4 Issue 6–June 2013
[2] Carlos Ordonez, "Improving Heart Disease Prediction Using Constrained Association Rules,"Seminar Presentation at University of Tokyo, 2004.
[3] Coronary Heart Diseases in India. Mark D Huffman. Center for Chronic Disease Control
[4] Srinivas, K., B.K. Rani, and A. Govrdhan, Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks. International Journal on Computer Science and Engineering (IJCSE), 2010. Vol. 02, No. 02: p. 250-255.
[5] Chen, J., Greiner, R.: Comparing Bayesian Network Classifiers. In Proc. of UAI-99, pp.101–108 ,1999.
[6] “Heart disease” from
[7] Richard N. Fogoros, M.D, The 9 Factors that Predict Heart Attack 90% of heart attacks are determined by these modifiable risk factors, Guide
[8] Sitar-Taut, V.A., et al., Using machine learning algorithms in cardiovascular disease risk evaluation. Journal of Applied Computer Science & Mathematics, 2009.
[9] Norberto Ezquerra and Rakesh Mullick. Perfex: An expert systemfor interpretingmyocardial perfusion. ExpertSystems with Applications, 6:455–468, 1993.
[10] Ramakrishnan Srikant and Rakesh Agrawal. Mining generalized association rules. In VLDB Conference, 1995. [11] Heckerman, D., A Tutorial on Learning With Bayesian Networks.1995, Microsoft Research.
[12]"Hospitalization for Heart Attack, Stroke, or Congestive Heart Failure among Persons with Diabetes", Special report: 2001 – 2003, New Mexico.
[13] Niti Guru, Anil Dahiya, Navin Rajpal, "Decision Support System for Heart Disease Diagnosis Using Neural Network", Delhi Business Review, Vol. 8, No. 1 (January - June 2007.
[14] T.K.Das,Arati Mohapatro, "A Study on Big Data Integration with Data Warehouse", International Journal of Computer Trends and Technology (IJCTT) – volume 9 number 4– Mar 2014
[15] Sellappan Palaniappan, Rafiah Awang, "Intelligent Heart Disease Prediction System Using Data Mining Techniques", IJCSNS International Journal of Computer Science and Network Security, Vol.8 No.8, August 2008.

Pruning-Classification Association Rule, Apriori algorithm, Naïve bayes