Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Gonçalves, F., Pereira, R., Ferreira, J., Vasconcelos, J. B., Melo, F. & Velez, I. (2018). Emergency waiting times data analysis. IAENG International Journal of Computer Science. 45 (3), 494-499
Exportar Referência (IEEE) 
F. Gonçalves et al.,  "Emergency waiting times data analysis", in IAENG Int. Journal of Computer Science, vol. 45, no. 3, pp. 494-499, 2018
Exportar BibTeX 
@article{gonçalves2018_1732722669000,
	author = "Gonçalves, F. and Pereira, R. and Ferreira, J. and Vasconcelos, J. B. and Melo, F. and Velez, I.",
	title = "Emergency waiting times data analysis",
	journal = "IAENG International Journal of Computer Science",
	year = "2018",
	volume = "45",
	number = "3",
	pages = "494-499",
	url = "http://www.iaeng.org/IJCS/"
}
Exportar RIS 
TY  - JOUR
TI  - Emergency waiting times data analysis
T2  - IAENG International Journal of Computer Science
VL  - 45
IS  - 3
AU  - Gonçalves, F.
AU  - Pereira, R.
AU  - Ferreira, J.
AU  - Vasconcelos, J. B.
AU  - Melo, F.
AU  - Velez, I.
PY  - 2018
SP  - 494-499
SN  - 1819-9224
UR  - http://www.iaeng.org/IJCS/
AB  - The Emergency Departments (ED) are a complex and important area of a hospital. With limited resources, it is mandatory to focus on efficiency. When hospitals are unable to deal with high demand, problems may
rise leading to longer waiting times and more dissatisfaction. In this research, the authors extracted knowledge from a hospital ED, through data analysis and data mining, applying Random Forest and Naïve Bayes to study the ED patient waiting time and diseases.
ER  -