Predicting plateau pressure in intensive medicine for ventilated patients

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 Ba...

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Detalhes bibliográficos
Autor principal: Oliveira, Sérgio (author)
Outros Autores: Portela, Filipe (author), Santos, Manuel (author), Machado, José Manuel (author), Abelha, António (author), Silva, Álvaro (author), Rua, Fernando (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2015
Assuntos:
Barotrauma
Plateau Pressure
Intensive Medicine
Data Mining
INTCare
Mechanical Ventilation
Science & Technology
Texto completo:http://hdl.handle.net/1822/39036
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/39036
Descrição
Resumo: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%.

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