Analysis of Demographic Characteristics Creating Coronary Artery Disease Susceptibility Using Random Forests Classifier

Author:

Akyol Kemal,Çalik Elif,Bayir Şafak,Şen Baha,Çavuşoğlu Abdullah

Publisher

Elsevier BV

Subject

General Engineering

Reference14 articles.

1. Abdullah AS, Rajalaxmi RR. A Data mining Model for predicting the Coronary Heart Disease using Random Forest Classifier. International Conference on Recent Trends in Computational Methods, Communication and Controls (ICON3C 2012); 2012. p. 23.

2. Akyol K, Şen B, Çalık, E, Analysis of Biochemistry and Hemogram Laboratory Test Results with Logistic Regression Method, Akademik Bilişim; 2012. p. 350-354.

3. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the Prospective Cardiovascular Münster(PROCAM) study;Assmann;Circulation,2002

4. Breiman L. Random forests. Machine Learning 2001; 45. p.18.

5. On the use of a logistic risk score in predicting risk of coronary heart disease;Chambless;Stat Med,1990

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