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Gonçalves, F., Pereira, R., Ferreira, J., Vasconcelos, J. B., Melo, F. & Velez, I. (2019). Predictive analysis in healthcare: emergency wait time prediction. In 9th International Symposium on Ambient Intelligence, ISAmI 2018. (pp. 138-145). Toledo: Springer.

F. Gonçalves et al.,  "Predictive analysis in healthcare: emergency wait time prediction", in 9th Int. Symp. on Ambient Intelligence, ISAmI 2018, Toledo, Springer, 2019, vol. 806, pp. 138-145

@inproceedings{gonçalves2019_1713923612253,
	author = "Gonçalves, F. and Pereira, R. and Ferreira, J. and Vasconcelos, J. B. and Melo, F. and Velez, I.",
	title = "Predictive analysis in healthcare: emergency wait time prediction",
	booktitle = "9th International Symposium on Ambient Intelligence, ISAmI 2018",
	year = "2019",
	editor = "",
	volume = "806",
	number = "",
	series = "",
	doi = "10.1007/978-3-030-01746-0_16",
	pages = "138-145",
	publisher = "Springer",
	address = "Toledo",
	organization = "",
	url = "https://link.springer.com/chapter/10.1007%2F978-3-030-01746-0_16"
}

TY  - CPAPER
TI  - Predictive analysis in healthcare: emergency wait time prediction
T2  - 9th International Symposium on Ambient Intelligence, ISAmI 2018
VL  - 806
AU  - Gonçalves, F.
AU  - Pereira, R.
AU  - Ferreira, J.
AU  - Vasconcelos, J. B.
AU  - Melo, F.
AU  - Velez, I.
PY  - 2019
SP  - 138-145
SN  - 2194-5357
DO  - 10.1007/978-3-030-01746-0_16
CY  - Toledo
UR  - https://link.springer.com/chapter/10.1007%2F978-3-030-01746-0_16
AB  - Emergency departments are an important area of a hospital, being the major entry point to the healthcare system. One of the most important issues regarding patient experience are the emergency department waiting times. In order to help hospitals improving their patient experience, the authors will perform a study where the Random Forest algorithm will be applied to predict emergency department waiting times. Using data from a Portuguese hospital from 2013 to 2017, the authors discretized the emergency waiting time in 5 different categories: “Really Low”, “Low”, “Average”, “High”, “Really High”. Plus, the authors considered as waiting time, the time from triage to observation. The authors expect to correctly evaluate the proposed classification algorithm efficiency and accuracy in order to be able to conclude if it is valuable when trying to predict ED waiting times. 
ER  -