Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

A Optimized Binary Approach for Heart Disease Decision Model in Biomedical Data Mining

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Sonika Rana, Sukhjot Kaur

Sonika Rana and Sukhjot Kaur. A Optimized Binary Approach for Heart Disease Decision Model in Biomedical Data Mining. International Journal of Computer Applications 156(12):1-5, December 2016. BibTeX

	author = {Sonika Rana and Sukhjot Kaur},
	title = {A Optimized Binary Approach for Heart Disease Decision Model in Biomedical Data Mining},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {12},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2016912411},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Heart diseases are the most common cause of death across worldwide. Due to the huge amount of data obtained from medical sector, hidden patterns remain hidden and knowledge cannot be extract from the database. This will result into loss of required information and treatment cannot be done accordingly. Several techniques have been proposed till now to find the effect of disease at earlier stage but still it is under consideration. Data mining is used to extract useful information from the database. Consequently, data analyses tool can be used to fetch required information from the database and effective decision can be made. Traditionally various heart disease detection techniques have been proposed like decision tree, genetic algorithm and so on.


  1. Kennedy, James. "Particle swarm optimization.", Springer, Pp. 760-766, 2011.
  2. Umair Shafique et al, “Data Mining in Healthcare for Heart Diseases”, International Journal of Innovation and Applied Studies, Vol. 10, No. 4, Pp. 1312-1322, Mar 2015.
  3. Sellappan Palaniappan et al, “Intelligent Heart Disease Prediction System Using Data Mining Techniques”, IEEE, Pp. 108-115.
  4. Hlaudi Daniel Masethe et al, “Prediction of Heart Disease using Classification Algorithms”, WCECS, Vol. 2, Pp. 22-24, October 2014
  5. Dušan teodorović1 et al, “Bee colony optimization – a cooperative learning approach to complex transportation problems”, Pp 51-60.
  6. Mandeep Kaur Bedi et al, “Comparative Study of Two Natural Phenomena”, International Journal of Scientific & Engineering Research, Vol.4, No. 3, March 2013
  7. Elham Shadkam et al, “Evaluation The Efficiency Of Cuckoo Optimization Algorithm”, International Journal on Computational Sciences & Applications, Vol.4, No.2, Pp. 39-47, April 2014
  8. Swagatam Das et al, “Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications
  9. Latha Parthiban et al, “Intelligent Heart Disease Prediction System using CANFIS and Genetic Algorithm”, International Journal of Biological and Medical Sciences, Pp. 157-160
  10. Christian Blum, “Ant colony optimization: Introduction and recent trends”, ELSEVIER, Pp. 353-373
  11. Rafael S. Parpinelli et al, “Data mining with an Ant Colony Optimization Algorithm
  12. T.Y. Chen et al, “Application of data mining in a global optimization algorithm”, ELSEVIER, Vol. 66, Pp. 24-63, December 2013
  13. K.Sudhakar et al, “Study of Heart Disease Prediction using Data Mining”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, No. 1, Pp. 1157-1160
  14. H Bosma et al, “Two alternative job stress models and the risk of coronary heart disease”, American Journal of Public Health January, Vol. 88, No. 1, pp. 68-74, 1988
  15. Punam Bajaj et al, “Review on Heart Disease Diagnosis Based on Data Mining Techniques”, IJSR, Vol. 3, No. 5, Pp. 1593-1596, May 2014
  16. Deepali Chandna, “Diagnosis of Heart Disease Using Data Mining Algorithm”, IJCSIT, Vol. 5, No. 2, Pp. 1678-1680, 2014
  17. Jyoti Soni et al, “Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction”, IJCA, Vol. 17, No. 8, Pp. 43-48, March 2011
  18. Asha Rajkumar et al, “Diagnosis of Heart Disease Using Data mining Algorithm”, Vol. 10, No. 10, Pp. 38-43, September 2010
  19. M. ANBARASI et al, “Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm”, IJEST, Vol. 2, No. 10, Pp. 5370-5376, 2010
  20. K.Srinivas et al, “Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks”, IJCSE, Vol. 2, No. 2, Pp. 250-255, 2010
  21. Nidhi Bhatla et al, “An Analysis of Heart Disease Prediction using Different Data Mining Techniques”, IJERT, Vol. 1, No. 8, Pp. 1-4, October 2012Heart
  22. Chaitrali S. Dangare et al, “A Data Mining Approach for Prediction of Heart Disease Using Neural Networks”, IJCET, Vol. 3, No. 3, December 2012
  23. K. Srinivas et al, “Analysis of coronary heart disease and prediction of heart attack in coal mining regions using data mining techniques”, IEEE, Pp. 1344-1349, Aug. 2010
  24. Yanwei Xing et al, “Combination Data Mining Methods with New Medical Data to Predicting Outcome of Coronary Heart Disease”, IEEE, Pp. 868-872, November 2007
  25. Monika Gandhi et al, “Predictions in heart disease using techniques of data mining”, IEEE, Pp. 520-525, February 2015
  26. Asha Rajkumar et al, “Diagnosis of Heart Disease Using Data mining Algorithm”, Vol. 10, No. 10, Pp. 38-43, September 2010.
  27. Chen, Guo-chu et al, "Particle swarm optimization algorithm.", information and control-shenyang, Vol 34, No.3, 2005, Pp. 318.
  28. Allender, Steven, et al. "Patterns of coronary heart disease mortality over the 20 th century in England and Wales: Possible plateaus in the rate of decline." BMC public health, Vol. 8, No.1, Pp. 1, 2008.
  29. Shi, Y., “Particle swarm optimization: developments”, IEEE, Vol. 1, pp. 81-86, 2001.
  30. Khanesar et al, “A novel binary particle swarm optimization”, pp. 1-6, IEEE, June 2007.


Data Mining, Heart Disease, BPSO, Neural Network.