Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid-base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters.

Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation

Mamandipoor, Behrooz;Osmani, Venet
2021

Abstract

Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid-base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters.
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Descrizione: Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/326646
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