Heart Disease Prediction Using Frequent Item Set Mining and Classification Technique
Автор: Sinkon Nayak, Mahendra Kumar Gourisaria, Manjusha Pandey, Siddharth Swarup Rautaray
Журнал: International Journal of Information Engineering and Electronic Business @ijieeb
Статья в выпуске: 6 vol.11, 2019 года.
Бесплатный доступ
The heart is the most important part of the human body. Any abnormality in heart results heart related illness in which it obstructs blood vessels which causes heart attack, chest pain or stroke. Care and improvement of the health by the help of identification, prevention, and care of any kind of diseases is the main goal. So for this various prediction analysis methods are used which job is to identify the illness at prelim phase so that prevention and care of heart disease is done. This paper emphasizes on the care of heart diseases at a primitive phase so that it will lead to a successful cure. In this paper, diverse data mining classification method like Decision tree classification, Naive Bayes classification, Support Vector Machine classification, and k-NN classification are used for determination and safeguard of the diseases.
Heart Disease, Frequent Itemset, Classification, Performance Measurement Parameter
Короткий адрес: https://sciup.org/15017068
IDR: 15017068 | DOI: 10.5815/ijieeb.2019.06.02
Список литературы Heart Disease Prediction Using Frequent Item Set Mining and Classification Technique
- Sundar, N. Aditya, P. Pushpa Latha, and M. Rama Chandra. "Performance analysis of classification data mining techniques over heart disease database." International journal of engineering science & advanced technology 2.3 (2012): 470-478.
- Palaniappan, Sellappan, and Rafiah Awang. "Intelligent heart disease prediction system using data mining techniques." 2008 IEEE/ACS international conference on computer systems and applications. IEEE, 2008.
- Dangare, Chaitrali S., and Sulabha S. Apte. "Improved study of heart disease prediction system using data mining classification techniques." International Journal of Computer Applications 47.10 (2012): 44-48.
- Thomas, J., and R. Theresa Princy. "Human heart disease prediction system using data mining techniques." 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT). IEEE, 2016.
- Wilson, Aswathy, et al. "Data Mining Techniques For Heart Disease Prediction." (2014).
- Banu, MA Nishara, and B. Gomathy. "Disease forecasting system using data mining methods." 2014 International conference on intelligent computing applications. IEEE, 2014.
- Waghulde, Nilakshi P., and Nilima P. Patil. "Genetic neural approach for heart disease prediction." International Journal of Advanced Computer Research 4.3 (2014): 778.
- Database: http://archive.ics.uci.edu/ml/ datasets/Heart+Disease
- Wu, Xindong, et al. "Data mining with big data." IEEE transactions on knowledge and data engineering 26.1 (2014): 97-107.
- Umadevi, S., and KS Jeen Marseline. "A survey on data mining classification algorithms." 2017 International Conference on Signal Processing and Communication (ICSPC). IEEE, 2017.
- Tomar, Divya, and Sonali Agarwal. "A survey on Data Mining approaches for Healthcare." International Journal of Bio-Science and Bio-Technology 5.5 (2013): 241-266.
- Krishnapuram, B., et al., A Bayesian approach to joint feature selection and classifier design.Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2004. 6(9): p. 1105-1111
- “Heart disease” from http://wikipedia.org
- Frawley and Piatetsky-Shapiro, 1996. Knowledge Discovery in Databases:An Overview. The AAAI/MIT Press, Menlo Park, C.A.
- "Hospitalization for Heart Attack, Stroke, or Congestive Heart Failure among Persons with Diabetes", Special report: 2001 – 2003, New Mexico.
- “ROC curve” from https://en.wikipedia.org
- “Decision Tree” from https://en.wikipedia.org
- “Naive Bayes” from https://en.wikipedia.org
- “Support Vector Machine” from https://en.wikipedia.org
- “K Nearest Neighbour” from https://en.wikipedia.org
