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Prediction of Cardiovascular Diseases using Support Vector Machine and Bayesian Classification
by
Prashasti Kanikar,
Disha Rajeshkumar Shah
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 156 - Number 2 |
| Year of Publication: 2016 |
| Authors: Prashasti Kanikar, Disha Rajeshkumar Shah |
10.5120/ijca2016912368
|
Prashasti Kanikar, Disha Rajeshkumar Shah . Prediction of Cardiovascular Diseases using Support Vector Machine and Bayesian Classification. International Journal of Computer Applications. 156, 2 ( Dec 2016), 9-13. DOI=10.5120/ijca2016912368
@article{
10.5120/ijca2016912368,
author = {
Prashasti Kanikar,
Disha Rajeshkumar Shah
},
title = { Prediction of Cardiovascular Diseases using Support Vector Machine and Bayesian Classification },
journal = {
International Journal of Computer Applications
},
issue_date = { Dec 2016 },
volume = { 156 },
number = { 2 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = {
9-13
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume156/number2/26679-2016912368/
},
doi = { 10.5120/ijca2016912368 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:01:29.336599+05:30
%A Prashasti Kanikar
%A Disha Rajeshkumar Shah
%T Prediction of Cardiovascular Diseases using Support Vector Machine and Bayesian Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 2
%P 9-13
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Cardiovascular disease is a broad team for a range of diseases affecting heart and blood vessels. Cardiovascular disease are the number one cause of death globally. The health care industry contains lots of medical data, therefore data mining techniques are required to discover hidden patterns and to make decision effectively in prediction of heart diseases. By applying data mining techniques, valuable knowledge can be extracted from health care systems. Data mining classification techniques like Naïve Bayesian and Support vector machine (SVM) are explained in this paper with their benefits and limitations. Data mining will help doctors to extract useful information from a huge dataset. In proposed research pre-processing uses techniques like noise removal, discarding records with missing data, filling default values if applicable and classification of attributes for decision making at different levels. This paper has predicted accuracy, specificity and sensitivity using a classifier. A classifier will predict whether a person has heart disease or not by using machine learning techniques like Support Vector Machine (SVM) and Naïve Bayes.
References
- K Raj Mohan, Ilango Paramasivam and Subhashini Sathya Narayan, “Prediction and Diagnosis of Cardio Vascular Disease– A Critical Survey”, published on Computing and Communication Technologies (WCCCT), 2014 World Congress on, pp.246-251, Feb. 27 2014-March 1 2014
- Minas A. Karaolis, Joseph A. Moutiris, Demetra Hadjipanayi, Constantinos S. Pattichis, “Assessment of the Risk Factors of Coronary Heart Events Based on Data Mining With Decision Trees”, IEEE Transactions On Information Technology In Biomedicine, VOL. 14, NO. 3, MAY 2010.
- T.John Peter, K. Somasundaram, “An Empirical Study on Prediction of Heart Disease Using Classification Data Mining Techniques”, IEEE, International conference on Advances in engineering, science and management, pp.514-518, 2012.
- Sulabha S.Apte and Chaitrali S.Dangare, “Improved Study of Heart Disease prediction System using Data Mining Classification Technique”, published in International Journal of Computer Applications(0975-888), Vol.47-No.10, June 2012
- Lovepreet Kaur, “Predicting Heart Disease Symptoms using Fuzzy C-Means Clustering”, published in International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 3 Issue 12, December 2014.
- Mythili T., Dev Mukherji, Nikita Padalia, and Abhiram Naidu “A Heart Disease Prediction Model using SVM- Decision Trees-Logistic Regression (SDL)”, IJCA, Vol.68- No.16 April 2013.
- Ranganatha S, Pooja Raj H.R., Anusha C and Vinay S.K., “Medical data mining and analysis for heart disease dataset using classification techniques”, published in IEEE National Conference on Challenges in Research & Technology in the Coming Decades (CRT 2013), , pp.1 – 5, 27-28 Sept. 2013.
- Alireza Kajabadi, Mohamad Hosein Saraee, and Sedighe Asgari., “Data Mining Cardiovascular Risk Factors”, published in Application of Information and Communication Technologies, 2009.AICT 2009.International Conference on, pp. 1-5,14-16 Oct.2009
- Yanwei Xing ,Jie Wang, Zhihong Zhao, and Yonghong Gao, “Combination Data Mining Methods with New Medical Data to Predicting Outcome of Coronary Heart Disease”, published in Convergence Information Technology, 2007. International Conference on, pp.868 – 872, 21-23 Nov. 2007.
- Chen, A.H., Huang, S.Y.; Hong, P.S.; Cheng, C.H.and Lin, E.J., “HDPS: Heart disease prediction system”, published in Computing in Cardiology, 2011, pp. 557 – 560, 18-21 Sept. 2011.
- Eman AbuKhousa, Piers Campbell, “Predictive Data Mining to Support Clinical Decisions: An Overview of Heart Disease Prediction Systems”, published in 2012 International Conference on Innovations in Information Technology (IIT),pp. 267 – 272, 18-20 March 2012.
- T.Georgeena.S. Thomas, Siddhesh.S. Budhkar, Siddhesh.K. Cheulkar, Akshay.B.Choudhary, Rohan Singh, “Heart Disease Diagnosis System Using Apriori Algorithm”, published in International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 2, February 2015.
- Aqueel Ahmed, Shaikh Abdul Hannan,“Data Mining Techniques to Find out Heart Diseases: An Overview”, published in International Journal of Innovative Technology and Exploring Engineering (IJITEE), Volume-1, Issue-4, September 2012.
- Shashikant Ghumbre,Chetn Patil and Ashok Ghatol, “Heart Disease Diagnosis Using Support Vector Machine”, International Conference on computer science and information Technology(ICCSIT 2011),Pattaya Dec.2011.
- Nidhi Bhatla,Kiran Jyoti, “An Analysis Of Heart Disease Prediction Using Different Data Mining Techniques”, International journal of engineering Research and Technology(IJERT),ISSN:2278-0181,Vol.1 Issue 8,October2012.
- S.Sivagowry,M.Durairaj; A.Persia, “ Am empirical study on applying data mining techniques for the analysis and prediction of heart diseases”, Published in Information Communication and Embedded Systems (ICICES), 2013 International Conference, pp.265-270,21-22 Feb 2013.
- Rajeev Gupta, KD Gupta, “Coronary Heart Disease in Low Socioeconomic Status Subjects in India -An Evolving Epidemic", 2009. [Online]. Available: http://indianheartjournal.com/ihj09/july_aug_09/358-367.html. [Accessed: 24-Aug-2015].
- Frawley and G.Piatetsky-shapiroa, “knowledge discovery in databases: An Overview”, published by the AAAI Press/ The MIT Press, Menlo Park, C.A.1996.
- Indian express news on heart disease. [Online]. Available: http://archive.indianexpress.com/news/india-set-to-be-heartdisease-capital-of-world--say-doctors/1009607. [Accessed: 24-Aug-2015]
- M. Bogl, W. Aigner, P. Filzmoser, T. Gschwandtner, T. Lammarsch, S. Miksch, and A. Rind, “Visual Analytics Methods to Guide Diagnostics for Time Series Model Predictions”, published in Proceedings of the 2014 IEEE VIS Workshop on Visualization for Predictive Analytics.
- Cardiovascular disease [Online]. Available: http://www.nhlbi.nih.gov/health/healthtopics/topics/cad/diagnosis. [Accessed : 25-Aug-2015]
- Coronary heart disease in Indians. [Online]. Available:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3028954 [Accessed: 25-Aug-2015]
- Jyoti Soni Ujma Ansari Dipesh Sharma and Sunita Soni, “Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction”, published in International Journal of Computer Applications, Volume 17– on 8, March 2011.
- Zhifang He and shuiping Chen, “Application of spss software on mental health education for community resident”, published in Computer Science & Education (ICCSE), 2015 10th International Conference on 22-24 July 2015, pp. 673 – 676.
- S.Florence1, Amma2, G.Annapoorani, K.Malathi, “Predicting the Risk of Heart Attacks using Neural Network and Decision Tree”, published in International Journal of Innovative Research in Computer and Communication Engineering, Vol. 2, Issue 11, November 2014.
- Ms. Priti V. Wadal, Dr. S. R. Gupta, “Predictive Data Mining For Medical Diagnosis: An Overview Of Heart Disease Prediction”, published in International Journal of Engineering Research and Applications and International Conference on Industrial Automation and Computing (ICIAC) on 12-13th April 2014.
- L. A. Muhammed, “Using data mining technique to diagnosis heart disease”, published in in Statistics in Science, Business, and Engineering (ICSSBE), 2012 International Conference, pp. 1-3,10-12 Sept. 2012.
- Carlos O., Edward O, Levien de Braal, and team “Mining Constrained Association Rules to Predict Heart Disease”, IEEE, International Conference on Data Mining p.433-440, 2001.
- Peter Harrington, “Machine Learning in Actions”, Published in April 16th 2012 by Manning Publications.
- Jiawei H. Micheline Kamber,"Data Mining,Concepts and techniques",SecondEdition,Elsevier,2006.
- UCI Machine Learning Repository. [Online]. Available: https://archive.ics.uci.edu/ml/datasets/Heart+Disease. [Accessed:27-April-2016 ]
Index Terms
Computer Science
Information Sciences
Keywords