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Reseach Article

Heart Disease Prediction System using Data Mining Techniques and Intelligent Fuzzy Approach: A Review

by V. Krishnaiah, G. Narsimha, N. Subhash Chandra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 2
Year of Publication: 2016
Authors: V. Krishnaiah, G. Narsimha, N. Subhash Chandra

V. Krishnaiah, G. Narsimha, N. Subhash Chandra . Heart Disease Prediction System using Data Mining Techniques and Intelligent Fuzzy Approach: A Review. International Journal of Computer Applications. 136, 2 ( February 2016), 43-51. DOI=10.5120/ijca2016908409

@article{ 10.5120/ijca2016908409,
author = { V. Krishnaiah, G. Narsimha, N. Subhash Chandra },
title = { Heart Disease Prediction System using Data Mining Techniques and Intelligent Fuzzy Approach: A Review },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 2 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 43-51 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016908409 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:35:59.445344+05:30
%A V. Krishnaiah
%A G. Narsimha
%A N. Subhash Chandra
%T Heart Disease Prediction System using Data Mining Techniques and Intelligent Fuzzy Approach: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 2
%P 43-51
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

The Healthcare trade usually clinical diagnosis is ended typically by doctor’s knowledge and practice. Computer Aided Decision Support System plays a major task in medical field. Data mining provides the methodology and technology to alter these mounds of data into useful information for decision making. By using data mining techniques it takes less time for the prediction of the disease with more accuracy. Among the increasing research on heart disease predicting system, it has happened to significant to categories the research outcomes and gives readers with an outline of the existing heart disease prediction techniques in each category. Data mining tools can answer trade questions that conventionally in use much time overriding to decide. In this paper we study different papers in which one or more algorithms of data mining used for the prediction of heart disease. As of the study it is observed that Fuzzy Intelligent Techniques increase the accuracy of the heart disease prediction system. The generally used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

  1. Gopal, S., and C. Woodcock, 1994. “Theory and Methods for Accuracy Assessment of Thematic Maps Using Fuzzy Sets”, Photogrammetric Engineering and Remote Sensing 60: Page No. 181-188.
  2. Shusaku Tsumoto,” Problems with Mining Medical Data”, 0-7695- 0792-1 I00@ 2000 IEEE.
  3. Y. Alp Aslandogan et. al.,” Evidence Combination in Medical Data Mining”, Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC’04) 0-7695-2108-8/04©2004 IEEE.
  4. Carlos Ordonez, "Improving Heart Disease Prediction Using Constrained Association Rules," Seminar Presentation at University of Tokyo, 2004.
  5. Franck Le Duff, Cristian Munteanb, Marc Cuggiaa, Philippe Mabob, "Predicting Survival Causes After Out of Hospital Cardiac Arrest using Data Mining Method", Studies in health technology and informatics, Vol. 107, No. Pt 2, page no. 1256-1259, 2004.
  6. Boleslaw Szymanski, Long Han, Mark Embrechts, Alexander Ross, Karsten Sternickel,Lijuan Zhu, "Using Efficient Supanova Kernel For Heart Disease Diagnosis", proc. ANNIE 06, intelligent engineering systems through artificial neural networks, vol. 16,page no. 305-310, 2006.
  7. Kiyong Noh, Heon Gyu Lee, Ho-Sun Shon, Bum Ju Lee, and Keun Ho Ryu, "Associative Classification Approach for Diagnosing Cardiovascular Disease", Springer 2006,Vol:345, page no. 721- 727.
  8. Heon Gyu Lee, Ki Yong Noh, Keun Ho Ryu, “Mining Biosignal Data: Coronary Artery Disease Diagnosis using Linear and Nonlinear Features of HRV,” LNAI 4819: Emerging Technologies in Knowledge Discovery and Data Mining, May 2007, page no. 56-66.
  9. 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.
  10. Hai Wang et. al.,”Medical Knowledge Acquisition through Data Mining”, Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education 978-1-4244- 2511-2/08©2008 Crown.
  11. Sellappan Palaniappan, Rafiah Awang, "Intelligent Heart Disease Prediction System Using Data Mining Techniques", (IJCSNS), Vol.8 No.8, August 2008.
  12. Latha Parthiban and R.Subramanian, "Intelligent Heart Disease Prediction System using CANFIS and Genetic Algorithm", International Journal of Biological, Biomedical and Medical Sciences, Vol. 3,Page No. 3, 2008.
  13. Harsh Vazirani et. al.," Use of Modular Neural Network for Heart Disease", Special Issue of IJCCT Vol.1 Issue 2, 3, 4; 2010 for International Conference [ACCTA-2010], 3-5 August 2010, page no. 88-93.
  14. Chaitrali S. Dangare et. al., “Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques”, (IJCA) (0975 – 8887), Vol. 47, No. 10, June 2012, page no. 44-48.
  15. S. Vijiyarani et. al., “An Efficient Classification Tree Technique for Heart Disease Prediction”, (ICRTCT - 2013) Proceedings published in (IJCA) (0975 – 8887), 2013, page no. 6-9.
  16. Victor-Emil Neagoe et. al., “A Neuro-Fuzzy Approach to Classification of ECG Signals for Ischemic Heart Disease Diagnosis”, AMIA Annu Symp Proc. 2003, page no. 494–498.
  17. Constantinos Koutsojannis et. al., “Using a Neurofuzzy Approach in Medical Application”, Springer- Verlag Berlin Heidelberg, 2007, page no. 477-484.
  18. Li SHI, Hui LI, Zhifu SUN, and Wei LIU,” Research on Diagnosing Heart Disease Using Adaptive Network-based Fuzzy Interferences System”, Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, USA, August 12-17, 2007, 1-4244-1 380-X/07/$25.00 ©2007 IEEE.
  19. Markos G. Tsipouras et. al., “Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling”, IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 12, NO. 4, JULY 2008.
  20. Ali.Adeli et. al., “A Fuzzy Expert System for Heart Disease Diagnosis", Proceedings of the international Multi Conference of Engineers and computer scientists 2010 Vol. 1, March 17- 19, 2010, Hong Kong, ISSN 2078-0966.
  21. A.Q. Ansari et. al., "Automated Diagnosis of Coronary Heart Disease Using Neuro-Fuzzy Integrated System", 2011 World Congress on Information and Communication Technologies 978-1-4673-0125-1@ 2011 IEEE, page no. 1383-1388.
  22. A.Anushya et. al., “A Comparative Study of Fuzzy Classifiers on Heart Data”, 978-1-4673-0132-91111$26.00@2011 IEEE, page no. 17-21.
  23. Nidhi Bhatla, Kiran Jyoti, “A Novel Approach for Heart Disease Diagnosis using Data Mining and Fuzzy Logic”, (IJCA), Volume 54– No.17, September 2012, ISSN 0975 – 8887, page no. 16-21.
  24. P.K. Anooj,”Clinical decision support system: Risk level prediction of heart disease using weighted fuzzy rules”, Journal of King Saud University – Computer and Information Sciences (2012) 24, Page No.27–40.
  25. Ashish Kumar Sen et. al., “A Data Mining Technique for Prediction of Coronary Heart Disease Using Neuro-Fuzzy Integrated Approach Two Level” (IJECS) (2319-7242), Volume 2 Issue 9 Sept., 2013 Page No. 2663-2671.
  26. R.Chitra, Dr.V.Seenivasagam, ” Heart Attack Prediction System Using Fuzzy C Means Classifier”. IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727, Volume 14, Issue 2 (Sep. - Oct. 2013), Page No. 23-31.
  27. Dr. A.V Senthil Kumar,” Diagnosis of heart disease using Advanced Fuzzy resolution Mechanism”. (IJSAIT), Vol.2, No.2, ISSN 2278-3083, Special Issue of ICCTE 2013, Page No. 22-30.
  28. K Cinetha et. al., “Decision Support System for Precluding Coronary Heart Disease (CHD) Using Fuzzy Logic”, (IJCST) – Volume 2 Issue 2, Mar-Apr 2014, ISSN: 2347-857, Page No.102-107.
  29. Upasana Juneja et. al., “Multi Parametric Approach Using Fuzzification on Heart Disease Analysis”, (IJESRT), Juneja et al., 3(5): May, 2014, ISSN: 2277-9655, Page No.492-497.
  30. Kantesh Kum ar Oad & Xu DeZhi,” A Fuzzy Rule based Approach to Predict Risk Level of Heart Disease”.(GJCST) (0975-4350), Volume 14 Issue 3 Version 1.0 Year 2014,Page No.17-22.
  31. Sharat Chandra, Ripu Ranjan Sinha,” “Fuzzy based Congestive Heart Failure Diagnosis and Analysis”, (IJCA) (0975 – 8887), Volume 105 – No. 6, November 2014, Page No.5-8.
  32. Y.Niranjana Devi, S.Anto ” An Evolutionary-Fuzzy Expert System for the Diagnosis of Coronary Artery Disease”. (IJARCET), ISSN: 2278 – 1323, Volume 3, Issue 4, April 2014, Page No.1478-1484.
  33. Shadab Adam Pattekari and Asma Parveen, “Prediction System for Heart Disease using Naïve Bayes”, International Journal of Advanced Computer and Mathematical Sciences (IJACMS), 2012.
  34. Carlos Ordonez, Edward Omiecinski, “Mining Constrained Association Rules to Predict Heart Disease”, IEEE. Published in International Conference on Data Mining (ICDM), page no. 433-440, 2001.
  35. Ms. Ishtake S.H ,Prof. Sanap S.A., “Intelligent Heart Disease Prediction System Using Data Mining Techniques”, International J. of Healthcare & Biomedical Research,2013.
  36. Ma.jabbar, Dr.prirti Chandra, B.L.Deekshatulu, “Cluster based Association rule mining for Heart Attack Prediction”, Journal of Theoretical and Applied Information Technology (JTAIT), 2011.
  37. Shantakumar B.Patil, Dr.Y.S. Kumaraswamy, “Extraction of Significant Patterns from Heart Disease Warehouses for Heart Attack Prediction”, (IJCSNS), 228 Security, 2009.
  38. Mohammad Taha Khan, Dr. Shamimul Qamar and Laurent F. Massin, “A Prototype of Cancer/Heart Disease Prediction Model Using Data Mining”, (IJAER), 2012.
  39. Humar Kahramanli, Novruz Allahverdi, “Design of a hybrid system for the diabetes and heart diseases”, Elsevier, 2008.
  40. M.Akhil jabbar, Dr.Priti Chandra, Dr.B.L Deekshatulu, “Heart Disease Prediction System using Associative Classification and Genetic Algorithm”, International Conference on Emerging Trends in Electrical, Electronics and Communication Technologies, 2012.
  41. Tom Dent, “Predicting the risk of coronary heart disease”, PHG foundation publisher, 2010.
  42. World Health Organization, “Global status report on no communicable diseases”, 2010.
Index Terms

Computer Science
Information Sciences


Heart disease Data mining techniques Fuzzy approach.