Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk

To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several deep learning architectures making use of attentio...

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Detalles Bibliográficos
Autores principales: Barbieri, Sebastiano, Kemp, James, Perez-Concha, Oscar, Kotwal, Sradha, Gallagher, Martin, Ritchie, Angus, Jorm, Louisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981230/
https://www.ncbi.nlm.nih.gov/pubmed/31980704
http://dx.doi.org/10.1038/s41598-020-58053-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981230/
https://www.ncbi.nlm.nih.gov/pubmed/31980704
http://dx.doi.org/10.1038/s41598-020-58053-z

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