A Data mining Model for predicting the Coronary Heart Disease using Random Forest Classifier
作者： A. Sheik Abdullah , R. R. Rajalaxmi
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摘要: Heart Disease (CHD) is a common form of disease affecting the heart and an important cause for premature death. From point view medical sciences, data mining involved in discovering various sorts metabolic syndromes. Classification techniques play significant role prediction exploration. technique such as Decision Trees has been used predicting accuracy events related to CHD. In this paper, Data model developed using Random Forest classifier improve investigate This can help practitioners CHD with its how it might be different segments population. The investigated are Angina, Acute Myocardial Infarction (AMI), Percutaneous Coronary Intervention (PCI), Artery Bypass Graft surgery (CABG). Experimental results have shown that classification algorithm successfully risk factors
ijcaonline.org参考文章(10)
C L Tsien, H S Fraser, R L Kennedy, W J Long, Using classification tree and logistic regression methods to diagnose myocardial infarction. Studies in health technology and informatics. pp. 493- 497 ,(1998) , 10.3233/978-1-60750-896-0-493
Zhiqiang Wang, Wendy E Hoy, Is the Framingham coronary heart disease absolute risk function applicable to Aboriginal people The Medical Journal of Australia. ,vol. 182, pp. 66- 69 ,(2005) , 10.5694/J.1326-5377.2005.TB06577.X
K. Srinivas, G. Raghavendra Rao, A. Govardhan, Analysis of coronary heart disease and prediction of heart attack in coal mining regions using data mining techniques international conference on computer science and education. pp. 1344- 1349 ,(2010) , 10.1109/ICCSE.2010.5593711
M. Atanasijević-Kunc, J. Drinovec, S. Ručigaj, A. Mrhar, Original article: Simulation analysis of coronary heart disease, congestive heart failure and end-stage renal disease economic burden Mathematics and Computers in Simulation. ,vol. 82, pp. 494- 507 ,(2011) , 10.1016/J.MATCOM.2010.10.024
Thomas D Rea, Susan R Heckbert, Robert C Kaplan, Nicholas L Smith, Rozenn N Lemaitre, Bruce M Psaty, None, Smoking status and risk for recurrent coronary events after myocardial infarction. Annals of Internal Medicine. ,vol. 137, pp. 494- 500 ,(2002) , 10.7326/0003-4819-137-6-200209170-00009
Sellappan Palaniappan, Rafiah Awang, Intelligent heart disease prediction system using data mining techniques acs/ieee international conference on computer systems and applications. pp. 108- 115 ,(2008) , 10.1109/AICCSA.2008.4493524
S.L. Elo, I.H. Karlberg, Validity and utilization of epidemiological data: A study of ischaemic heart disease and coronary risk factors in a local population Public Health. ,vol. 123, pp. 52- 57 ,(2009) , 10.1016/J.PUHE.2008.07.010
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 bioinformatics and bioengineering. ,vol. 14, pp. 559- 566 ,(2010) , 10.1109/TITB.2009.2038906
Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni, Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction International Journal of Computer Applications. ,vol. 17, pp. 43- 48 ,(2011) , 10.5120/2237-2860
P. Rajeswari, G.Sophia Reena, Analysis of Liver Disorder Using Data mining Algorithm Global journal of computer science and technology. ,vol. 10, ,(2010)