Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS
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oai:localhost:PNK-70472023-03-22T03:03:27Z Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS Ludmilla, Penarrubia Aude, Verstraete Maciej, Orkisz computed tomography positive end-expiratory pressure CC BY 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 respiratory distress syndrome (ARDS). The aim of this study was to assess both intra- and inter-observer smallest real difference (SRD) exceeding measurement error of recruitment using both human and machine learning-made lung segmentation (i.e., delineation) on CT. This single-center observational study was performed on adult ARDS patients. CT were acquired at end-expiration and end-inspiration at the PEEP level selected by clinicians, and at end-expiration at PEEP 5 and 15 cmH2O. 2023-03-22T03:03:27Z 2023-03-22T03:03:27Z 2023 Book https://link.springer.com/article/10.1186/s40635-023-00495-6 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7047 en application/pdf Springer |
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computed tomography positive end-expiratory pressure |
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computed tomography positive end-expiratory pressure Ludmilla, Penarrubia Aude, Verstraete Maciej, Orkisz Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS |
description |
CC BY |
format |
Book |
author |
Ludmilla, Penarrubia Aude, Verstraete Maciej, Orkisz |
author_facet |
Ludmilla, Penarrubia Aude, Verstraete Maciej, Orkisz |
author_sort |
Ludmilla, Penarrubia |
title |
Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS |
title_short |
Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS |
title_full |
Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS |
title_fullStr |
Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS |
title_full_unstemmed |
Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS |
title_sort |
precision of ct-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ards |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1186/s40635-023-00495-6 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7047 |
_version_ |
1761097140392689664 |
score |
8.891053 |