Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/16840
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Campo DCValorIdioma
dc.contributor.authorGonçalves, F.-
dc.contributor.authorPereira, R.-
dc.contributor.authorFerreira, J.-
dc.contributor.authorVasconcelos, J. B.-
dc.contributor.authorMelo, F.-
dc.contributor.authorVelez, I.-
dc.date.accessioned2018-12-05T16:06:12Z-
dc.date.available2018-12-05T16:06:12Z-
dc.date.issued2019-
dc.identifier.isbn978-303001745-3-
dc.identifier.issn2194-5357-
dc.identifier.urihttps://ciencia.iscte-iul.pt/id/ci-pub-52079-
dc.identifier.urihttp://hdl.handle.net/10071/16840-
dc.description.abstractEmergency 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.eng
dc.language.isoeng-
dc.publisherSpringer-
dc.relationUID/MULTI/0446/2013-
dc.rightsopenAccess-
dc.subjectBig dataeng
dc.subjectEmergency departmenteng
dc.subjectHealthcareeng
dc.subjectPredictive analyticseng
dc.titlePredictive analysis in healthcare: emergency wait time predictioneng
dc.typeconferenceObject-
dc.event.typeConferênciapt
dc.event.locationToledoeng
dc.event.date2018-
dc.pagination138 - 145-
dc.peerreviewedyes-
dc.journal9th International Symposium on Ambient Intelligence, ISAmI 2018-
dc.volume806-
degois.publication.firstPage138-
degois.publication.lastPage145-
degois.publication.locationToledoeng
degois.publication.titlePredictive analysis in healthcare: emergency wait time predictioneng
dc.description.versioninfo:eu-repo/semantics/acceptedVersion-
dc.identifier.doi10.1007/978-3-030-01746-0_16-
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.date.embargo2019-12-05
Aparece nas coleções:ISTAR-CRI - Comunicações a conferências internacionais

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