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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2023
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| Materias: | |
| 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 |