@article{(Open Science Index):https://publications.waset.org/pdf/10001221,
	  title     = {A Medical Resource Forecasting Model for Emergency Room Patients with Acute Hepatitis},
	  author    = {R. J. Kuo and  W. C. Cheng and  W. C. Lien and  T. J. Yang},
	  country	= {},
	  institution	= {},
	  abstract     = {Taiwan is a hyper endemic area for the Hepatitis B
virus (HBV). The estimated total number of HBsAg carriers in the
general population who are more than 20 years old is more than 3
million. Therefore, a case record review is conducted from January
2003 to June 2007 for all patients with a diagnosis of acute hepatitis
who were admitted to the Emergency Department (ED) of a
well-known teaching hospital. The cost for the use of medical
resources is defined as the total medical fee. In this study, principal
component analysis (PCA) is firstly employed to reduce the number of
dimensions. Support vector regression (SVR) and artificial neural
network (ANN) are then used to develop the forecasting model. A total
of 117 patients meet the inclusion criteria. 61% patients involved in
this study are hepatitis B related. The computational result shows that
the proposed PCA-SVR model has superior performance than other
compared algorithms. In conclusion, the Child-Pugh score and
echogram can both be used to predict the cost of medical resources for
patients with acute hepatitis in the ED.
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {5},
	  year      = {2015},
	  pages     = {377 - 382},
	  ee        = {https://publications.waset.org/pdf/10001221},
	  url   	= {https://publications.waset.org/vol/101},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 101, 2015},