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Predicting Prolonged Apnea During Nurse-Administered Procedural Sedation: Machine Learning Study.

Aaron ConwayCarla R JungquistKristina ChangNavpreet KambojJoanna R SutherlandSebastian MafeldMatteo Parotto
Published in: JMIR perioperative medicine (2021)
Decision curve analysis indicated that using a random forest model would lead to a better outcome for capnography alarm management than using an aggressive strategy in which alarms are triggered after 15 seconds of apnea. The model would not be superior to the conservative strategy in which alarms are only triggered after 30 seconds.
Keyphrases
  • machine learning
  • obstructive sleep apnea
  • primary care
  • climate change
  • mechanical ventilation
  • artificial intelligence
  • intensive care unit
  • big data
  • extracorporeal membrane oxygenation