A hybrid data envelopment analysis—artificial neural network prediction model for COVID-19 severity in transplant recipients

In an overwhelming demand scenario, such as the SARS-CoV-2 pandemic, pressure over health systems may outburst their predicted capacity to deal with such extreme situations. Therefore, in order to successfully face a health emergency, scientific evidence and validated models are needed to provide re...

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Detalles Bibliográficos
Autores principales: Revuelta, Ignacio, Santos-Arteaga, Francisco J., Montagud-Marrahi, Enrique, Ventura-Aguiar, Pedro, Di Caprio, Debora, Cofan, Frederic, Cucchiari, David, Torregrosa, Vicens, Piñeiro, Gaston Julio, Esforzado, Nuria, Bodro, Marta, Ugalde-Altamirano, Jessica, Moreno, Asuncion, Campistol, Josep M., Alcaraz, Antonio, Bayès, Beatriu, Poch, Esteban, Oppenheimer, Federico, Diekmann, Fritz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062617/
https://www.ncbi.nlm.nih.gov/pubmed/33907345
http://dx.doi.org/10.1007/s10462-021-10008-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062617/
https://www.ncbi.nlm.nih.gov/pubmed/33907345
http://dx.doi.org/10.1007/s10462-021-10008-0

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