Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed an artificial neural network using textual (e.g. patient history) and tabular (e.g. laboratory values) data from ED electronic medical reports. The pr...

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Detalles Bibliográficos
Autores principales: Dipaola, Franca, Gatti, Mauro, Giaj Levra, Alessandro, Menè, Roberto, Shiffer, Dana, Faccincani, Roberto, Raouf, Zainab, Secchi, Antonio, Rovere Querini, Patrizia, Voza, Antonio, Badalamenti, Salvatore, Solbiati, Monica, Costantino, Giorgio, Savevski, Victor, Furlan, Raffaello
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322913/
https://www.ncbi.nlm.nih.gov/pubmed/37407595
http://dx.doi.org/10.1038/s41598-023-37512-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322913/
https://www.ncbi.nlm.nih.gov/pubmed/37407595
http://dx.doi.org/10.1038/s41598-023-37512-3

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