Predicting plateau pressure in intensive medicine for ventilated patients
Main Author: | |
---|---|
Publication Date: | 2015 |
Other Authors: | , , , , , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/1822/39036 |
Summary: | 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 cm2O) 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%. |
id |
RCAP_d3355b543bb81ad942f0ddbde29a6ca0 |
---|---|
oai_identifier_str |
oai:repositorium.sdum.uminho.pt:1822/39036 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
Predicting plateau pressure in intensive medicine for ventilated patientsBarotraumaPlateau PressureIntensive MedicineData MiningINTCareMechanical VentilationScience & TechnologyBarotrauma 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 cm2O) 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%.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).SpringerUniversidade do MinhoOliveira, SérgioPortela, FilipeSantos, ManuelMachado, José ManuelAbelha, AntónioSilva, ÁlvaroRua, Fernando20152015-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/39036engOliveira, 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).978-3-319-16527-12194-535710.1007/978-3-319-16528-8_17info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T04:44:54Zoai:repositorium.sdum.uminho.pt:1822/39036Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:57:20.128480Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Predicting plateau pressure in intensive medicine for ventilated patients |
title |
Predicting plateau pressure in intensive medicine for ventilated patients |
spellingShingle |
Predicting plateau pressure in intensive medicine for ventilated patients Oliveira, Sérgio Barotrauma Plateau Pressure Intensive Medicine Data Mining INTCare Mechanical Ventilation Science & Technology |
title_short |
Predicting plateau pressure in intensive medicine for ventilated patients |
title_full |
Predicting plateau pressure in intensive medicine for ventilated patients |
title_fullStr |
Predicting plateau pressure in intensive medicine for ventilated patients |
title_full_unstemmed |
Predicting plateau pressure in intensive medicine for ventilated patients |
title_sort |
Predicting plateau pressure in intensive medicine for ventilated patients |
author |
Oliveira, Sérgio |
author_facet |
Oliveira, Sérgio Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António Silva, Álvaro Rua, Fernando |
author_role |
author |
author2 |
Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António Silva, Álvaro Rua, Fernando |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Oliveira, Sérgio Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António Silva, Álvaro Rua, Fernando |
dc.subject.por.fl_str_mv |
Barotrauma Plateau Pressure Intensive Medicine Data Mining INTCare Mechanical Ventilation Science & Technology |
topic |
Barotrauma Plateau Pressure Intensive Medicine Data Mining INTCare Mechanical Ventilation Science & Technology |
description |
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 cm2O) 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%. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/39036 |
url |
http://hdl.handle.net/1822/39036 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
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). 978-3-319-16527-1 2194-5357 10.1007/978-3-319-16528-8_17 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833595000360796160 |