Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning mod...

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Detalles Bibliográficos
Autores principales: Lassau, Nathalie, Ammari, Samy, Chouzenoux, Emilie, Gortais, Hugo, Herent, Paul, Devilder, Matthieu, Soliman, Samer, Meyrignac, Olivier, Talabard, Marie-Pauline, Lamarque, Jean-Philippe, Dubois, Remy, Loiseau, Nicolas, Trichelair, Paul, Bendjebbar, Etienne, Garcia, Gabriel, Balleyguier, Corinne, Merad, Mansouria, Stoclin, Annabelle, Jegou, Simon, Griscelli, Franck, Tetelboum, Nicolas, Li, Yingping, Verma, Sagar, Terris, Matthieu, Dardouri, Tasnim, Gupta, Kavya, Neacsu, Ana, Chemouni, Frank, Sefta, Meriem, Jehanno, Paul, Bousaid, Imad, Boursin, Yannick, Planchet, Emmanuel, Azoulay, Mikael, Dachary, Jocelyn, Brulport, Fabien, Gonzalez, Adrian, Dehaene, Olivier, Schiratti, Jean-Baptiste, Schutte, Kathryn, Pesquet, Jean-Christophe, Talbot, Hugues, Pronier, Elodie, Wainrib, Gilles, Clozel, Thomas, Barlesi, Fabrice, Bellin, Marie-France, Blum, Michael G. B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840774/
https://www.ncbi.nlm.nih.gov/pubmed/33504775
http://dx.doi.org/10.1038/s41467-020-20657-4

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