CFP last date
20 December 2024
Reseach Article

Applying Data Mining Technique for Predicting Incubator Length of Stay in Egypt and USA

by Hagar Fady S., Taha El-sayed T., Mervat Mahmoud M.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 71 - Number 8
Year of Publication: 2013
Authors: Hagar Fady S., Taha El-sayed T., Mervat Mahmoud M.
10.5120/12379-8726

Hagar Fady S., Taha El-sayed T., Mervat Mahmoud M. . Applying Data Mining Technique for Predicting Incubator Length of Stay in Egypt and USA. International Journal of Computer Applications. 71, 8 ( June 2013), 21-28. DOI=10.5120/12379-8726

@article{ 10.5120/12379-8726,
author = { Hagar Fady S., Taha El-sayed T., Mervat Mahmoud M. },
title = { Applying Data Mining Technique for Predicting Incubator Length of Stay in Egypt and USA },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 71 },
number = { 8 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 21-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume71/number8/12379-8726/ },
doi = { 10.5120/12379-8726 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:35:01.574749+05:30
%A Hagar Fady S.
%A Taha El-sayed T.
%A Mervat Mahmoud M.
%T Applying Data Mining Technique for Predicting Incubator Length of Stay in Egypt and USA
%J International Journal of Computer Applications
%@ 0975-8887
%V 71
%N 8
%P 21-28
%D 2013
%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 in Egypt and USA, in addition to define factors affecting Length of Stay (LOS) of preterm infants and their severity of impact. This study has relied on data collected from both Egypt and US, to compare LOS's driving factors and the accuracy of LOS prediction in both countries. The obtained results indicated that accurate and early diagnosis may speed up treatment and thus reduce length of stay.

References
  1. R. Bellaz and B. Zupan, "Predictive data mining in clinical medicine: Current issues and guidelines," International Journal of Medical Informatics, vol. 77, no. 2, pp. 81-97, February 2008.
  2. H. Koh and G. Tan, "Data Mining Applications In Healthcare," J. Health. Info. Man, vol. 19, no. 2, pp. 64-72, 2005.
  3. 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.
  4. J. Sandham, "Baby Incubation," 2008. [Online]. Available: http://www. ebme. co. uk.
  5. B. Zerinkow and K. Holtmannspötter, "Predicting Length-Of-Stay In Preterm Neonates," European Journal of Pediatrics, vol. 158, no. 1, 1999.
  6. 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.
  7. 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.
  8. 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.
  9. EGNN, "Egyptian Neonatal Network," [Online]. Available: http://www. egynewborn. net.
  10. National Hospital Discharge Survey, 2002, Michigan: Inter-University Consortium for Political and Social Research, 2002.
  11. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), Center of Disea Control, 2008.
  12. EGNN, "Dataset Manual," EGNN, Cairo, 2010.
  13. EGNN, "28 Day/Discharge Form," EGNN, Cairo, 2010.
  14. R. Haberstroh, Oracle® Data Mining Tutorial for Oracle Data Mining 11g Release 1, Oracle, 2008.
  15. M. Clinic, "Infant jaundice," Mayo Foundation for Medical Education and Research;, 2011. [Online]. Available: http://www. mayoclinic. com/health/infant-jaundice.
  16. J. Zurada and S. Lonial, "Comparison Of The Performance Of Several Data Mining Methods For Bad Debt Recovery In The Healthcare Industry," The Journal of Applied Business Research, vol. 21, no. 2, Spring 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Length of Stay Data Mining Regression Incubator Premature