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Reseach Article

A Novel Approach for Heart Disease Diagnosis using Data Mining and Fuzzy Logic

by Nidhi Bhatla, Kiran Jyoti
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 17
Year of Publication: 2012
Authors: Nidhi Bhatla, Kiran Jyoti
10.5120/8658-2498

Nidhi Bhatla, Kiran Jyoti . A Novel Approach for Heart Disease Diagnosis using Data Mining and Fuzzy Logic. International Journal of Computer Applications. 54, 17 ( September 2012), 16-21. DOI=10.5120/8658-2498

@article{ 10.5120/8658-2498,
author = { Nidhi Bhatla, Kiran Jyoti },
title = { A Novel Approach for Heart Disease Diagnosis using Data Mining and Fuzzy Logic },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 17 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number17/8658-2498/ },
doi = { 10.5120/8658-2498 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:56.452648+05:30
%A Nidhi Bhatla
%A Kiran Jyoti
%T A Novel Approach for Heart Disease Diagnosis using Data Mining and Fuzzy Logic
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 17
%P 16-21
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cardiovascular disease is a term used to describe a variety of heart diseases, illnesses, and events that impact the heart and circulatory system. A clinician uses several sources of data and tests to make a diagnostic impression but it is not necessary that all the tests are useful for the diagnosis of a heart disease. The objective of our work is to reduce the number of attributes used in heart disease diagnosis that will automatically reduce the number of tests which are required to be taken by a patient. Our work also aims at increasing the efficiency of the proposed system. The observations illustrated that Decision Tree and Naive Bayes using fuzzy logic has outplayed over other data mining techniques.

References
  1. 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, 27–40.
  2. E. P. Ephzibah, Dr. V. Sundarapandian, "Framing Fuzzy Rules using Support Sets for Effective Heart Disease Diagnosis"; International Journal of Fuzzy Logic Systems (IJFLS) Vol. 2, No. 1, February 2012.
  3. A. Sudha, P. Gayathri, N. Jaisankar, "Utilization of Data mining Approaches for Prediction of Life Threatening Diseases Survivability"; International Journal of Computer Applications (0975 – 8887) Volume 41– No. 17, March 2012.
  4. Chaitrali S. Dangare, Sulabha S. Apte, "Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques"; International Journal of Computer Applications (0975 – 888) Volume 47– No. 10, June 2012.
  5. 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.
  6. E. Sivasankar, Dr. R. S. Rajesh, "Knowledge Discovery in Medical Datasets Using a Fuzzy Logic rule based Classifier"; 978-1-4244-7406-6/10/$26. 00, IEEE, 2010.
  7. M. A. Saleem Durai, et. al. "Effective analysis and diagnosis of lung cancer using fuzzy rules"; International Journal of Engineering Science and Technology Vol. 2(6), 2102-2108, 2010.
  8. Mostafa Fathi Ganji, Mohammad Saniee Abadeh, "Using fuzzy Ant Colony Optimization for Diagnosis of Diabetes Disease"; Proceedings of ICEE 2010, May 11-13, 2010, 978-1-4244-6760-0/10/$26. 00©2010 IEEE.
  9. Huang Hai, "Data Mining Based on a Compensative Fuzzy Neural Network"; International Conference On Computer Design And Applications (ICCDA), 2010.
  10. M. A. Saleem Durai, N. Ch. S. N. Iyengar, "Effective Analysis and Diagnosis of Lung Cancer Using Fuzzy Rules"; International Journal of Engineering Science and Technology, Vol. 2(6), 2010.
  11. 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.
  12. Rupa G. Mehta, Dipti P. Rana, Mukesh A. Zaveri, "A Novel Fuzzy Based Classification for Data Mining using Fuzzy Discretization"; World Congress on Computer Science and Information Engineering, 2009.
  13. 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.
  14. Sellappan Palaniappan, Rafiah Awang, "Intelligent Heart Disease Prediction System Using Data Mining Techniques"; 978-1-4244-1968-5/08/$25. 00©2008 IEEE.
  15. Latha Parthiban, R. Subramanian, "Intelligent Heart Disease Prediction System using CANFIS and Genetic Algorithm"; International Journal of Biological and Life Sciences 3:3 2007.
  16. Niti Guru, et al. "Decision Support System for Heart Disease Diagnosis Using Neural Network"; Delhi Business Review, Vol. 8, No. 1, 2007.
  17. Kemal Polata, Salih Gunesa, Sulayman Tosunb, "Diagnosis of heart disease using artificial immune recognition system and fuzzy weighted pre-processing"; Elsevier , Pattern recognation, 2007.
  18. Harleen Kaur, Siri Krishan Wasan, "Empirical Study on Applications of Data Mining Techniques in Healthcare"; Journal of Computer Science 2 (2): 194-200, 2006.
  19. Carlos Ordonez, "Comparing association rules and decision trees for disease prediction"; ACM, 2006.
  20. 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, pp:305-310, 2006.
  21. Kiyong Noh, Heon Gyu Lee, Ho-Sun Shon, Bum Ju Lee, and Keun Ho Ryu, "Associative Classification Approach for Diagnosing Cardiovascular Disease"; Springer, Vol:345, pp: 721- 727, 2006.
  22. Cleveland database: http://archive. ics. uci. edu/ml/datasets/Heart+Disease
  23. Han, J. , Kamber, M, "Data Mining Concepts and Techniques"; Morgan Kaufmann Publishers, 2006.
  24. American Heart Association. Heart Disease and Stroke Statistics — 2004 Update. Dallas, Tex. : American Heart Association; 2003.
  25. Statlog database: http://archive. ics. uci. edu/ml/machine-learning-databases/statlog/heart
Index Terms

Computer Science
Information Sciences

Keywords

Cardiovascular disease data mining fuzzy logic weka tool decision tree naive bayes classification via clustering