Temporal convolutional networks and data rebalancing for clinical length of stay and mortality prediction

It is critical for hospitals to accurately predict patient length of stay (LOS) and mortality in real-time. We evaluate temporal convolutional networks (TCNs) and data rebalancing methods to predict LOS and mortality. This is a retrospective cohort study utilizing the MIMIC-III database. The MIMIC-E...

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Detalles Bibliográficos
Autores principales: Bednarski, Bryan P., Singh, Akash Deep, Zhang, Wenhao, Jones, William M., Naeim, Arash, Ramezani, Ramin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732283/
https://www.ncbi.nlm.nih.gov/pubmed/36481828
http://dx.doi.org/10.1038/s41598-022-25472-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732283/
https://www.ncbi.nlm.nih.gov/pubmed/36481828
http://dx.doi.org/10.1038/s41598-022-25472-z

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