Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/39036

Full metadata record
DC FieldValueLanguage
dc.contributor.authorOliveira, Sérgiopor
dc.contributor.authorPortela, Filipepor
dc.contributor.authorSantos, Manuelpor
dc.contributor.authorMachado, José Manuelpor
dc.contributor.authorAbelha, Antóniopor
dc.contributor.authorSilva, Álvaropor
dc.contributor.authorRua, Fernandopor
dc.date.accessioned2015-12-15T18:17:30Z-
dc.date.issued2015-
dc.identifier.citationOliveira, S., Portela, F., Santos, M. F., Machado, J., Abelha, A., Silva, Á., & Rua, F. (2015) Predicting plateau pressure in intensive medicine for ventilated patients. Vol. 354. Advances in Intelligent Systems and Computing (pp. 179-188).por
dc.identifier.isbn978-3-319-16527-1-
dc.identifier.isbn978-3-319-16528-8-
dc.identifier.issn2194-5357por
dc.identifier.urihttp://hdl.handle.net/1822/39036-
dc.description.abstractBarotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm𝐻2O) in a real environment and using real data. The present study explored and assessed the possibility of predicting the Plateau pressure class with high accuracies. The dataset used only contained data provided by the ventilators. The best models are able to predict the Plateau Pressure with an accuracy ranging from 95.52% to 98.71%.por
dc.description.sponsorshipThis work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013. The authors would like to thank FCT (Foundation of Science and Technology, Portugal) for the financial support through the contract PTDC/EEI-SII/1302/2012 (INTCare II).por
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/126314/PTpor
dc.rightsopenAccess-
dc.subjectBarotraumapor
dc.subjectPlateau Pressurepor
dc.subjectIntensive Medicinepor
dc.subjectData Miningpor
dc.subjectINTCarepor
dc.subjectMechanical Ventilationpor
dc.titlePredicting plateau pressure in intensive medicine for ventilated patientspor
dc.typeconferencePaperpor
dc.peerreviewedyespor
oaire.citationStartPage179por
oaire.citationEndPage188por
oaire.citationTitleAdvances in Intelligent Systems and Computingpor
oaire.citationVolume354por
dc.identifier.doi10.1007/978-3-319-16528-8_17por
dc.subject.wosScience & Technologypor
sdum.journalAdvances in Intelligent Systems and Computingpor
sdum.conferencePublicationNEW CONTRIBUTIONS IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2por
sdum.bookTitleAdvances in Intelligent Systems and Computingpor
Appears in Collections:CCTC - Artigos em revistas internacionais
CAlg - Livros e capítulos de livros/Books and book chapters

Files in This Item:
File Description SizeFormat 
2015 - AISC - Predicting Plateau Pressure in Intensive Medicine for Ventilated Patients.pdf443,92 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID