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BioMed Research International
Volume 2017, Article ID 3292849, 12 pages
https://doi.org/10.1155/2017/3292849
Research Article

Improving Prediction Accuracy of “Central Line-Associated Blood Stream Infections” Using Data Mining Models

1Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
2Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
3Clinical Epidemiology & Infection Control, Faculty of Nursing, King Abdulaziz University, Jeddah, Saudi Arabia
4Department of Computer Science and Software Engineering, University of Hail, Hail, Saudi Arabia

Correspondence should be addressed to Abdul Hamid M. Ragab; as.ude.uak@bagara

Received 1 March 2017; Revised 23 July 2017; Accepted 30 July 2017; Published 20 September 2017

Academic Editor: Hesham H. Ali

Copyright © 2017 Amin Y. Noaman 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

Amin Y. Noaman, Farrukh Nadeem, Abdul Hamid M. Ragab, et al., “Improving Prediction Accuracy of “Central Line-Associated Blood Stream Infections” Using Data Mining Models,” BioMed Research International, vol. 2017, Article ID 3292849, 12 pages, 2017. https://doi.org/10.1155/2017/3292849.