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Using machine learning models to predict oxygen saturation following ventilator support adjustment in critically ill children: A single center pilot study.

Sam GhazalMichaël SauthierDavid W BrossierWassim BouachirPhilippe A JouvetRita Noumeir
Published in: PloS one (2019)
This single center pilot study using machine learning predictive model resulted in an algorithm with poor accuracy. The comparison of machine learning models showed that bagged complex trees was a promising approach. However, there is a need to improve these models before incorporating them into a clinical decision support systems. One potentially solution for improving predictive model, would be to increase the amount of data available to limit over-fitting that is potentially one of the cause for poor classification performances for 2 of the three class labels.
Keyphrases
  • machine learning
  • clinical decision support
  • electronic health record
  • deep learning
  • big data
  • artificial intelligence
  • young adults
  • acute respiratory distress syndrome
  • mechanical ventilation