Research Article
Applying Data Mining Technique for the Optimal Usage of Neonatal Incubator
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 52 - Issue 3 |
| Published: August 2012 |
| Authors: Hagar Fady S., Taha El-Sayed T., Mervat Mahmoud M. |
10.5120/8181-1508
|
Hagar Fady S., Taha El-Sayed T., Mervat Mahmoud M. . Applying Data Mining Technique for the Optimal Usage of Neonatal Incubator. International Journal of Computer Applications. 52, 3 (August 2012), 11-20. DOI=10.5120/8181-1508
@article{ 10.5120/8181-1508,
author = { Hagar Fady S.,Taha El-Sayed T.,Mervat Mahmoud M. },
title = { Applying Data Mining Technique for the Optimal Usage of Neonatal Incubator },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 52 },
number = { 3 },
pages = { 11-20 },
doi = { 10.5120/8181-1508 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Hagar Fady S.
%A Taha El-Sayed T.
%A Mervat Mahmoud M.
%T Applying Data Mining Technique for the Optimal Usage of Neonatal Incubator%T
%J International Journal of Computer Applications
%V 52
%N 3
%P 11-20
%R 10.5120/8181-1508
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This research aims to provide intelligent tool to predict incubator Length of Stay (LOS) of infants which shall increase the utilization and management of infant incubators. The data sets of Egyptian Neonatal Network (EGNN) were employed and Oracle Data Miner (ODM) tool was used for the analysis and prediction of data. The obtained results indicated that data mining technique is an appropriate and sufficiently sensitive method to predict required LOS of premature and ill infant.
References
- A. Almazyad, M. Ahamad and M. Siddiqui, "Effective Hypertensive Treatment Using Data Mining In Saudi Arabia," J. CLIN. MONITOR. COMP. , vol. 24, no. 2, 2010.
- H. Koh and G. Tan, "Data Mining Applications In Healthcare," J. Health. Info. Man, vol. 19, no. 2, pp. 64-72, 2005.
- J. Soni, U. Ansari, D. Sharma and S. Soni, "Predictive Data Mining for Medical Diagnosis:An Overview of Heart Disease Prediction," J. Comp. Appl. , vol. 17, no. 8, Mar 2011.
- WHO, "Newborn deaths decrease but account for higher share of global child deaths," 2011. [Online]. Available: http://www. who. int/mediacentre/news/releases/2011/newborn_deaths_20110830/en/index. html.
- J. Sandham, "Baby Incubation," 2008. [Online]. Available: http://www. ebme. co. uk.
- B. Zerinkow and K. Holtmannspötter, "Predicting Length-Of-Stay In Preterm Neonates," European Journal of Pediatrics, vol. 158, no. 1, 1999.
- S. Hintz, C. Bann, N. Ambalavanan, M. Cotten, A. Das and R. Higgins, "Predicting Time to Hospital Discharge for Extremely Preterm Infants," Journal of the American Academy of Pediatrics, vol. 125, pp. 146-154, 2010.
- P. Liu, L. Lei, J. Yin, W. Zhang, W. Naijun and E. El-Darzi, "Healthcare Data Mining: Prediction Inpatient Length of Stay," in 3rd International IEEE Conference on Intelligent Systems, Aveiro, 2006.
- G. Kraljevic and S. Gotovac, "Modeling Data Mining Applications for Prediction of Prepaid Churn in Telecommunication Services," Automatika, vol. 51, no. 3, pp. 275-283, 2010.
- EGNN, "Egyptian Neonatal Network," [Online]. Available: http://www. egynewborn. net.
- EGNN, "28 Day/Discharge Form," EGNN, Cairo, 2010.
- EGNN, "Dataset Manual," EGNN, Cairo, 2010.
- R. Haberstroh, Oracle® Data Mining Tutorial for Oracle Data Mining 11g Release 1, Oracle, 2008.
- A. Ben-Hur and J. Weston, A User's Guide to Support Vector Machines.
- Oracle, "Introducing Oracle Data Mining, Oracle Data Mining Concepts 11g Release 1 (11. 1)," [Online]. Available: http://docs. oracle. com/cd/B28359_01/datamine. 111/b28129/intro_concepts. htm.
- M. Clinic, "Infant jaundice," Mayo Foundation for Medical Education and Research;, 2011. [Online]. Available: http://www. mayoclinic. com/health/infant-jaundice.
- Oracle Data Mining Concepts, 11g Release 1 (11. 1), Oracle, 2008.
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