COVID-19 pneumonia: prediction of patient outcome by CT-based quantitative lung parenchyma analysis combined with laboratory parameters
To evaluate the prognostic value of fully automatic lung quantification based on spectral computed tomography (CT) and laboratory parameters for combined outcome prediction in COVID-19 pneumonia.
Gespeichert in:
| Hauptverfasser: | , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
July 29, 2022
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| In: |
PLOS ONE
Year: 2022, Jahrgang: 17, Heft: 7, Pages: 1-5 |
| ISSN: | 1932-6203 |
| DOI: | 10.1371/journal.pone.0271787 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1371/journal.pone.0271787 Verlag, kostenfrei, Volltext: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0271787 
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| Verfasserangaben: | Thuy D. Do, Stephan Skornitzke, Uta Merle, Maximilian Kittel, Stefan Hofbaur, Claudius Melzig, Hans-Ulrich Kauczor, Mark O. Wielpütz, Oliver Weinheimer |
MARC
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| 520 | |a To evaluate the prognostic value of fully automatic lung quantification based on spectral computed tomography (CT) and laboratory parameters for combined outcome prediction in COVID-19 pneumonia. | ||
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| 650 | 4 | |a Gas analysis | |
| 650 | 4 | |a Pneumonia | |
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| 650 | 4 | |a Virus testing | |
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