Classification Utility & Procedures for Recognition of Heart Disease: A Review

Authors

  • Manoj Raman  M.Tech. Scholar, Department of Computer Science & Engineering, RIET, Jaipur, Rajasthan, India
  • Vijay Kumar Sharma  Asst. Prof., Department of Computer Science & Engineering, RIET, Jaipur, Rajasthan, India

Keywords:

Data mining, Naive bayes, Neural Network, Decision Trees

Abstract

Nowadays, among several the heart diseases became as the most life killer diseases around the globe. In human body heart is a most significant muscular organ which pumps blood through the blood vessels. Only accurate and speedy prediction of this disease will help to prevent from it. However a lot of approaches have introduced to aid the professionals but each and every algorithm has associates their unique challenges. This paper presents start of the art work of heart disease prediction system supported by data mining and fusion of intelligent techniques.

References

  1. Humar Kahramanli, Novruz Allahverdi "Design of a hybrid system for the diabetes and heart diseases", ELSEVIER, Expert Systems with Applications 35 (2008). pp.no. 82?89.
  2. Anil Jain and Douglas Zongker "Feature Selection: Evaluation, Application, and Small Sample Performance" IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 19, No. 2, February 1997. pp.no. 153-158.
  3. 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, pp. 56-66, May 2007.
  4. Li, W., Han, 1., Pei, 1.: “CMAR: Accurate and Efficient Classification Based on Multiple Association Rules”. In: Proc. of 2001 International Conference on Data Mining, 2001.
  5. Mrudula Gudadhe, Kapil Wankhade and Snehlata Dongre "Decision Support System for Heart Disease based on Support Vector Machine and Artificial Neural Network" International Conference on Computer and Communication Technology (ICCCT), IEEE. 2010. p.p no. - 741-745.
  6. Niti Guru, Anil Dahiya and NavinRajpal “Decision support system for heart diseases prediction using neural networks” Delhi Business Review Vol. 8, No. 1,PP 1-6 (January - June 2007).
  7. 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, pp. 1256-9, 2004.
  8. 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.
  9. Carlos Ordonez, "Improving Heart Disease Prediction Using Constrained Association Rules," Seminar Presentation at University of Tokyo, 2004.
  10. ?Boleslaw Szmanski, Long Han, Mark Embrechts, Alexander Ross, Karsten Sternickel, Lijuan Zhu, “Using Efficeint Supanova Kernel For Heart Disease Diagnosis”. Proc. ANNIE 06, intelligent engineering systems through artificial neural networks, vol. 16, pp:305-310, 2006.
  11. Latha Parthiban and R.Subramanian “Intelligent heart Diseases Prediction System Using CANFIS and Genetic Algorithm” International Journal of Biological, Biomedical and Medical Sciences 3.3.2008.
  12. ?John Peter “An Empirical Study On Prediction Of Heart Disease Using Classification Data Mining Techniques” IEEE-International Conference On Advances In Engineering, Science And Management PP. 514-517(ICAESM -2012) March 30, 31, 2012.
  13. Maryam Tayefia ,Mohammad Tajfard, Sara Saffar, Parichehr Hanachi, Ali Reza Amirabadizadeh , Habibollah Esmaeily, Ali Taghipour, Gordon A. Ferns, Mohsen Moohebati, Majid Ghayour-Mobarhan "hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm" Computer Methods and Programs in Biomedicine, ELSEVIER, 141 (2017) pp.no -105?109
  14. S Silvia Priscila, M Hemalatha "Diagnosis of heart disease with particle bee-neural network" Special Section:Computational Life Sciences and Smarter Technological Advancement. Biomed Res- India 2017 Volume Special Issue. Pp.no-1-7
  15. Xiao Liu, Xiaoli Wang, Qiang Su, Mo Zhang, Yanhong Zhu, Qiugen Wang and QianWang ?A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method, Hindawi Computational and Mathematical Methods in Medicine Volume 2017,pp.no. 1-11.

International Journal of Scientific Research in Science and Technology

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Published

2017-12-31

Issue

Volume 3, Issue 8, November-December-2017

Section

Research Articles

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How to Cite

[1]
Manoj Raman, Vijay Kumar Sharma, " Classification Utility & Procedures for Recognition of Heart Disease: A Review, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 8, pp.383-387, November-December-2017.