Publicação em atas de evento científico Q3
Predictive analysis in healthcare: emergency wait time prediction
Filipe Gonçalves (Gonçalves, F.); Rúben Pereira (Pereira, R.); Joao C Ferreira or Joao Ferreira (Ferreira, J.); José Braga Vasconcelos (Vasconcelos, J. B.); Fernando Melo (Melo, F.); Iria Velez (Velez, I.);
9th International Symposium on Ambient Intelligence, ISAmI 2018
Ano
2019
Língua
Inglês
País
Suíça
Mais Informação
Scopus

N.º de citações: 2

(Última verificação: 2021-01-19 16:05)

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: 1.6
Abstract/Resumo
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.
Agradecimentos/Acknowledgements
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Palavras-chave
Big data,Emergency department,Healthcare,Predictive analytics
  • Ciências da Computação e da Informação - Ciências Naturais
  • Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UID/MULTI/0446/2013 Fundação para a Ciência e a Tecnologia