Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS
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| Ngôn ngữ: | English |
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Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1186/s40635-023-00495-6 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7047 |
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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 |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
computed tomography positive end-expiratory pressure |
| spellingShingle |
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 |
8.893527 |