Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS

Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS

Abstract Background Assessing measurement error in alveolar recruitment on computed tomography (CT) is of paramount importance to select a reliable threshold identifying patients with high potential for alveolar recruitment and to rationalize positive end-expiratory pressure (PEEP) setting in acute...

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Bibliographic Details
Main Authors: Ludmilla Penarrubia, Aude Verstraete, Maciej Orkisz, Eduardo Davila, Loic Boussel, Hodane Yonis, Mehdi Mezidi, Francois Dhelft, William Danjou, Alwin Bazzani, Florian Sigaud, Sam Bayat, Nicolas Terzi, Mehdi Girard, Laurent Bitker, Emmanuel Roux, Jean-Christophe Richard
Format: Article
Language:English
Published: SpringerOpen 2023-02-01
Series:Intensive Care Medicine Experimental
Subjects:
Acute respiratory distress syndrome
Computed tomography
Alveolar recruitment
Bias
Repeatability
Reproducibility
Online Access:https://doi.org/10.1186/s40635-023-00495-6

Internet

https://doi.org/10.1186/s40635-023-00495-6

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