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Computational and Mathematical Methods in Medicine
Volume 2015 (2015), Article ID 576413, 6 pages
http://dx.doi.org/10.1155/2015/576413
Research Article

Application of Random Forest Survival Models to Increase Generalizability of Decision Trees: A Case Study in Acute Myocardial Infarction

1Regional Knowledge Hub and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman 7616911317, Iran
2Department of Epidemiology, University of Tehran, Tehran, Iran
3Research Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman 7616911317, Iran

Received 12 September 2015; Revised 23 November 2015; Accepted 24 November 2015

Academic Editor: Issam El Naqa

Copyright © 2015 Iman Yosefian et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Iman Yosefian, Ehsan Mosa Farkhani, and Mohammad Reza Baneshi, “Application of Random Forest Survival Models to Increase Generalizability of Decision Trees: A Case Study in Acute Myocardial Infarction,” Computational and Mathematical Methods in Medicine, vol. 2015, Article ID 576413, 6 pages, 2015. doi:10.1155/2015/576413