Personalized predictions of patient outcomes during and after hospitalization using artificial intelligence

Hospital systems, payers, and regulators have focused on reducing length of stay (LOS) and early readmission, with uncertain benefit. Interpretable machine learning (ML) may assist in transparently identifying the risk of important outcomes. We conducted a retrospective cohort study of hospitalizati...

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Detalles Bibliográficos
Autores principales: Hilton, C. Beau, Milinovich, Alex, Felix, Christina, Vakharia, Nirav, Crone, Timothy, Donovan, Chris, Proctor, Andrew, Nazha, Aziz
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/PMC7125114/
https://www.ncbi.nlm.nih.gov/pubmed/32285012
http://dx.doi.org/10.1038/s41746-020-0249-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125114/
https://www.ncbi.nlm.nih.gov/pubmed/32285012
http://dx.doi.org/10.1038/s41746-020-0249-z

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