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
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.