Computer Science & Electrical

Computer Science & Electrical

Prediction of heart disease using data mining techniques: A Case study

Pages: 11  ,  Volume: 41  ,  Issue: 1 , November   2019
Received: 04 Dec 2019  ,  Published: 24 December 2019
Views: 72  ,  Download: 22

Authors

# Author Name
1 Shamim Hasnanin Shadid
2 Ahmed Shafkat
3 Ms. Fauzia Yasmeen
4 Sabbir Ahmed Sibli
5 Md. Rumman Rafi

Abstract

Data mining is the process of rearranging through large datasets to identify patterns and establish relationships between them to solve problems through data analysis. Data mining tools allow enterprise to predict future trends. A pattern is useful, interesting and easily understood by human if it is valid for a given test and with some degree of certainty. Though the data amount generated in predicting heart disease is huge and complex advance data mining techniques can process the data. Heart disease is one the disease that causes the maximum causalities. This problem is identified long before but no proper actions been taken to combat this problem. This paper set out goal to finding which method would be best for predicting the diseases using data of four different dataset from four different places. Therefore, this article tries to finding which method would be best for predicting the diseases using data of four different datasets from four different places. This is a comparative study on the efficiency of different data mining techniques such as Decision Tree (DT), K-Nearest Neighbor (kNN), Naive Bayes, Logistic Regression in predicting heart diseases. The Data Mining techniques are analyzed and the accuracy of prediction is noted for each method used. The result showed that heart diseases can be predicted with accuracy of above 80%.

Keywords

References

  1. Syed Immamul Ansarullah, Pradeep Kumar Sharma, Abdul  Wahid, Mudasir M Kirmani “Heart Disease Prediction  System using Data Mining Techniques: A study”  International Research Journal of Engineering and  Technology (IRJET) Volume: 03 Issue: 08 , Aug-2016.
  2. Abhishek Taneja “Heart Disease Prediction System Using  Data Mining Techniques”ORIENTAL JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY ISSN: 0974-6471 Vol. 6, No. (4): December 2013.
  3. Andrea D’Souza.”Heart Disease Prediction Using Data Mining Techniques” International Journal of Research in Engineering and Science (IJRES) ISSN (Online): 2320-9364, Volume 3 Issue 3 ? March 15.
  4. Nidhi Bhatla, Kiran Jyoti, “ An Analysis of Heart Disease  Prediction using Different Data Mining Techniques” International Journal of Engineering and Technology Vol.1 issue 8 2012.
  5. Beant Kaur and Williamjeet Singh.,” Review on Heart Disease Prediction System using Data Mining Techniques”, IJRITCC ,October 2014.             
  6. R. Chitra, Review Of Heart Disease Prediction System Using Data Mining And Hybrid Intelligent Techniques; Ictact Journal On Soft Computing, July 2013,volume: 03, Issue: 04.
  7. Carlos Ordonez, "Improving Heart Disease Prediction Using Constrained Association Rules," Seminar Presentation at University of Tokyo, 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. 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.
  10. 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, No. 3, 2008.
  11. Clevelanddatabase:http://archive.ics.uci.edu/ml/dataets/Heart+Disease.