Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS.
Ludmilla PenarrubiaAude VerstraeteMaciej OrkiszEduardo DavilaLoic BousselHodane YonisMehdi MezidiFrancois DhelftWilliam DanjouAlwin BazzaniFlorian SigaudSam BayatNicolas TerziMehdi GirardLaurent BitkerEmmanuel RouxJean-Christophe RichardPublished in: Intensive care medicine experimental (2023)
). Human-machine and human-human inter-observer measurement errors with CT are of similar magnitude, suggesting that machine learning segmentation algorithms are credible alternative to humans for quantifying alveolar recruitment on CT.
Keyphrases
- machine learning
- endothelial cells
- deep learning
- induced pluripotent stem cells
- computed tomography
- pluripotent stem cells
- contrast enhanced
- image quality
- magnetic resonance imaging
- artificial intelligence
- positron emission tomography
- big data
- magnetic resonance
- extracorporeal membrane oxygenation
- acute respiratory distress syndrome
- pet ct
- mechanical ventilation