Finding the best trade-off between performance and interpretability in predicting hospital length of stay using structured and unstructured data

OBJECTIVE: This study aims to develop high-performing Machine Learning and Deep Learning models in predicting hospital length of stay (LOS) while enhancing interpretability. We compare performance and interpretability of models trained only on structured tabular data with models trained only on unst...

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Detalles Bibliográficos
Autores principales: Jaotombo, Franck, Adorni, Luca, Ghattas, Badih, Boyer, Laurent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688642/
https://www.ncbi.nlm.nih.gov/pubmed/38032876
http://dx.doi.org/10.1371/journal.pone.0289795

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688642/
https://www.ncbi.nlm.nih.gov/pubmed/38032876
http://dx.doi.org/10.1371/journal.pone.0289795

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