Development and multicentric external validation of a prognostic COVID-19 severity model based on thoracic CT
Risk stratification of COVID-19 patients can support therapeutic decisions, planning and resource allocation in the hospital. In times of high incidence, a prognostic model based on data efficiently retrieved from one source can enable fast decision support.
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2025
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| In: |
BMC medical informatics and decision making
Year: 2025, Jahrgang: 25, Pages: 1-15 |
| ISSN: | 1472-6947 |
| DOI: | 10.1186/s12911-025-02983-z |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/s12911-025-02983-z
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| Verfasserangaben: | Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Hichem Sahli, Nikos Deligiannis, Emma Verelst, Bart Ilsen, Simon Van Eyndhoven, Lucie Seyler, Arne Witdouck, Gilles Darcis, Julien Guiot, Athanasios Giannakis and Jef Vandemeulebroucke |
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| 520 | |a Risk stratification of COVID-19 patients can support therapeutic decisions, planning and resource allocation in the hospital. In times of high incidence, a prognostic model based on data efficiently retrieved from one source can enable fast decision support. | ||
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