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Chest-X-ray is a mainstay for follow-up in critically ill patients with covid-19 induced pneumonia.

作者信息

de Barry Olivier, Obadia Ilan, El Hajjam Mostafa, Carlier Robert-Yves

机构信息

DMU Smart Imaging, Medical Imaging Department. Assistance Publique-Hôpitaux de Paris, GH Université Paris-Saclay, Ambroise Paré Teaching Hospital, 92100 Boulogne-Billancourt, France; DMU Smart Imaging, Medical Imaging Department. Assistance Publique-Hôpitaux de Paris, GH Université Paris-Saclay, Raymond Poincaré Teaching Hospital, 92380 Garches, France.

DMU Smart Imaging, Medical Imaging Department. Assistance Publique-Hôpitaux de Paris, GH Université Paris-Saclay, Ambroise Paré Teaching Hospital, 92100 Boulogne-Billancourt, France.

出版信息

Eur J Radiol. 2020 Aug;129:109075. doi: 10.1016/j.ejrad.2020.109075. Epub 2020 May 13.

DOI:10.1016/j.ejrad.2020.109075
PMID:32405142
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7219396/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97ca/7219396/f715366c004f/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97ca/7219396/f715366c004f/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97ca/7219396/f715366c004f/gr1_lrg.jpg

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本文引用的文献

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Radiology. 2020 Aug;296(2):E72-E78. doi: 10.1148/radiol.2020201160. Epub 2020 Mar 27.
2
Mediastinal Emphysema, Giant Bulla, and Pneumothorax Developed during the Course of COVID-19 Pneumonia.在 COVID-19 肺炎的病程中发生了纵隔气肿、巨大肺大疱和气胸。
Korean J Radiol. 2020 May;21(5):541-544. doi: 10.3348/kjr.2020.0180. Epub 2020 Mar 20.
3
Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study.
便携式胸部X光片：对新冠肺炎重症患者的福音
Cureus. 2023 Mar 18;15(3):e36330. doi: 10.7759/cureus.36330. eCollection 2023 Mar.
4
Automated Diagnosis of Chest X-Ray for Early Detection of COVID-19 Disease.基于胸部 X 光的 COVID-19 疾病早期检测的自动化诊断。
Comput Math Methods Med. 2021 Oct 21;2021:6919483. doi: 10.1155/2021/6919483. eCollection 2021.
5
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis.使用迁移学习和判别相关分析进行深度融合的CCSHNet对COVID-19的分类
Inf Fusion. 2021 Apr;68:131-148. doi: 10.1016/j.inffus.2020.11.005. Epub 2020 Nov 13.
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Determining extent of COVID-19 pneumonia on CT based on biological variables.基于生物学变量确定 COVID-19 肺炎的严重程度 CT 检查。
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