Thông tin tài liệu


Nhan đề : 
Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS
Tác giả : 
Ludmilla, Penarrubia
Aude, Verstraete
Maciej, Orkisz
Năm xuất bản : 
2023
Nhà xuất bản : 
Springer
Tóm tắt : 
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.
Mô tả: 
CC BY
URI: 
https://link.springer.com/article/10.1186/s40635-023-00495-6
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7047
Bộ sưu tập
OER- Y học- Điều dưỡng
XEM MÔ TẢ

19

XEM TOÀN VĂN

54

Danh sách tệp tin đính kèm: