DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning

Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging availability of streaming electronic health record...

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Detalles Bibliográficos
Autores principales: Shickel, Benjamin, Loftus, Tyler J., Adhikari, Lasith, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra, Rashidi, Parisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372608/
https://www.ncbi.nlm.nih.gov/pubmed/30755689
http://dx.doi.org/10.1038/s41598-019-38491-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372608/
https://www.ncbi.nlm.nih.gov/pubmed/30755689
http://dx.doi.org/10.1038/s41598-019-38491-0

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