Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/39036
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Campo DC | Valor | Idioma |
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dc.contributor.author | Oliveira, Sérgio | por |
dc.contributor.author | Portela, Filipe | por |
dc.contributor.author | Santos, Manuel | por |
dc.contributor.author | Machado, José Manuel | por |
dc.contributor.author | Abelha, António | por |
dc.contributor.author | Silva, Álvaro | por |
dc.contributor.author | Rua, Fernando | por |
dc.date.accessioned | 2015-12-15T18:17:30Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Oliveira, 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.isbn | 978-3-319-16527-1 | - |
dc.identifier.isbn | 978-3-319-16528-8 | - |
dc.identifier.issn | 2194-5357 | por |
dc.identifier.uri | https://hdl.handle.net/1822/39036 | - |
dc.description.abstract | Barotrauma 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.sponsorship | This 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.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147280/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876-PPCDTI/126314/PT | por |
dc.rights | openAccess | - |
dc.subject | Barotrauma | por |
dc.subject | Plateau Pressure | por |
dc.subject | Intensive Medicine | por |
dc.subject | Data Mining | por |
dc.subject | INTCare | por |
dc.subject | Mechanical Ventilation | por |
dc.title | Predicting plateau pressure in intensive medicine for ventilated patients | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationStartPage | 179 | por |
oaire.citationEndPage | 188 | por |
oaire.citationTitle | Advances in Intelligent Systems and Computing | por |
oaire.citationVolume | 354 | por |
dc.identifier.doi | 10.1007/978-3-319-16528-8_17 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Advances in Intelligent Systems and Computing | por |
sdum.conferencePublication | NEW CONTRIBUTIONS IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2 | por |
sdum.bookTitle | Advances in Intelligent Systems and Computing | por |
Aparece nas coleções: | CCTC - Artigos em revistas internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2015 - AISC - Predicting Plateau Pressure in Intensive Medicine for Ventilated Patients.pdf | 443,92 kB | Adobe PDF | Ver/Abrir |