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Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction

by Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 17 - Number 8
Year of Publication: 2011
Authors: Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni

Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni . Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction. International Journal of Computer Applications. 17, 8 ( March 2011), 43-48. DOI=10.5120/2237-2860

@article{ 10.5120/2237-2860,
author = { Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni },
title = { Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction },
journal = { International Journal of Computer Applications },
issue_date = { March 2011 },
volume = { 17 },
number = { 8 },
month = { March },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { },
doi = { 10.5120/2237-2860 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:05:06.163716+05:30
%A Jyoti Soni
%A Ujma Ansari
%A Dipesh Sharma
%A Sunita Soni
%T Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 17
%N 8
%P 43-48
%D 2011
%I Foundation of Computer Science (FCS), NY, USA

The successful application of data mining in highly visible fields like e-business, marketing and retail has led to its application in other industries and sectors. Among these sectors just discovering is healthcare. The healthcare environment is still ‘information rich’ but ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. This research paper intends to provide a survey of current techniques of knowledge discovery in databases using data mining techniques that are in use in today’s medical research particularly in Heart Disease Prediction. Number of experiment has been conducted to compare the performance of predictive data mining technique on the same dataset and the outcome reveals that Decision Tree outperforms and some time Bayesian classification is having similar accuracy as of decision tree but other predictive methods like KNN, Neural Networks, Classification based on clustering are not performing well. The second conclusion is that the accuracy of the Decision Tree and Bayesian Classification further improves after applying genetic algorithm to reduce the actual data size to get the optimal subset of attribute sufficient for heart disease prediction.

  1. Asha Rajkumar, G.Sophia Reena, Diagnosis Of Heart Disease Using Datamining Algorithm, Global Journal of Computer Science and Technology 38 Vol. 10 Issue 10 Ver. 1.0 September 2010.
  2. Sunita Soni, O.P.Vyas, Using Associative Classifiers for Predictive Analysis in Health Care Data Mining, International Journal of Computer Application (IJCA, 0975 – 8887) Volume 4– No.5, July 2010, pages 33-34.
  3. K.Srinivas, B.Kavihta Rani , A.Govrdhan , Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks, (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 02, 2010, 250-255.
  4. M. ANBARASI, E. ANUPRIYA, N.CH.S.N.IYENGAR, Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm, International Journal of Engineering Science and Technology Vol. 2(10), 2010, 5370-5376
  5. N.A. Setiawan, P.A. Venkatachalam, and Ahmad Fadzil M.H. , Rule Selection for Coronary Artery Disease Diagnosis Based on Rough Set, International Journal of Recent Trends in Engineering, Vol 2, No. 5, November 2009.
  6. Sunita Soni , Jyothi Pillai, O.P.Vyas, An Associative Classifier Using Weighted Association Rule , IEEE proceedings of the World Congress on Nature and Biologically Inspired Computing (NaBIC'09), December 09-11, 2009, 1492-1496.
  7. Shantakumar B.Patil, Y.S.Kumaraswamy, Intelligent and Effective Heart Attack Prediction System Using Data Mining and Artificial Neural Network, European Journal of Scientific Research ISSN 1450-216X Vol.31 No.4 (2009), pp.642-656
  9. 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
  10. Fadi Thabtah, A review of associative classification mining, The Knowledge Engineering Review, Volume 22 , Issue 1 (March 2007),Pages 37-65, 2007.
  11. Carloz Ordonez, Association Rule Discovery with Train and Test approach for heart disease prediction, IEEE Transactions on Information Technology in Biomedicine, Volume 10, No. 2, April 2006.pp 334-343.
  12. Harleen Kaur , Siri Krishan Wasan and Vasudha Bhatnagar, THE IMPACT OF DATA MINING TECHNIQUES ON MEDICAL DIAGNOSTICS, Data Science Journal, Volume 5, 19 October 2006 pp119-126.
  13. Yin, X., Han, J. CPAR: Classification based on predictive association rule. In Proceedings of the SIAM International Conference on Data Mining. San Francisco, CA: SIAM Press, 2003, pp. 369-376.
  14. Feng Tao, Fionn Murtagh, Mohsen Farid. Weighted Association Rule Mining using Weighted Support and Significance Framework, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining 2003, Pages:661-666 Year of Publication: 2003
  15. W.Li, J. Han, J.Pei , CMAR- Classification based on Multiple Association Rules, ICDM’01, , San Jose, CA, Nov. 2001. pp. 369-376
  16. W. Wang, J. Yang and P. Yu. Efficient mining of weighted association rules (WAR), Proc. of the ACM SIGKDD Conf. on Knowledge Discovery and Data Mining, 270-274, 2000.
  17. Liu,B, Hsu. W. Ma, Integrating Classification and association rule mining . Proceeding of the KDD, 1998(CBA) pp 80-86.
  18. Magnus Stensmo, Terrence J. Sejnowski Automated Medical Diagnosis based on Decision Theory and Learning from Cases, World Congress on Neural Networks 1996 International Neural Network society pp. 1227-1 231.
  19. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In VLDB'94, , Santiago, Chile, Sept. 1994. pp. 487-49
Index Terms

Computer Science
Information Sciences


KNN Neural Networks Bayesian classification Classification based on clustering Decision Tree