A real-time integrated framework to support clinical decision making for covid-19 patients

BACKGROUND: The COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of t...

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Detalles Bibliográficos
Autores principales: Murri, Rita, Masciocchi, Carlotta, Lenkowicz, Jacopo, Fantoni, Massimo, Damiani, Andrea, Marchetti, Antonio, Sergi, Paolo Domenico Angelo, Arcuri, Giovanni, Cesario, Alfredo, Patarnello, Stefano, Antonelli, Massimo, Bellantone, Rocco, Bernabei, Roberto, Boccia, Stefania, Calabresi, Paolo, Cambieri, Andrea, Cauda, Roberto, Colosimo, Cesare, Crea, Filippo, De Maria, Ruggero, De Stefano, Valerio, Franceschi, Francesco, Gasbarrini, Antonio, Landolfi, Raffaele, Parolini, Ornella, Richeldi, Luca, Sanguinetti, Maurizio, Urbani, Andrea, Zega, Maurizio, Scambia, Giovanni, Valentini, Vincenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800500/
https://www.ncbi.nlm.nih.gov/pubmed/35158181
http://dx.doi.org/10.1016/j.cmpb.2022.106655

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800500/
https://www.ncbi.nlm.nih.gov/pubmed/35158181
http://dx.doi.org/10.1016/j.cmpb.2022.106655

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