A Bayesian approach to predictive uncertainty in chemotherapy patients at risk of acute care utilization

BACKGROUND: Machine learning (ML) predictions are becoming increasingly integrated into medical practice. One commonly used method, ℓ(1)-penalised logistic regression (LASSO), can estimate patient risk for disease outcomes but is limited by only providing point estimates. Instead, Bayesian logistic...

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Detalles Bibliográficos
Autores principales: Fanconi, Claudio, de Hond, Anne, Peterson, Dylan, Capodici, Angelo, Hernandez-Boussard, Tina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250586/
https://www.ncbi.nlm.nih.gov/pubmed/37269570
http://dx.doi.org/10.1016/j.ebiom.2023.104632

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10250586/
https://www.ncbi.nlm.nih.gov/pubmed/37269570
http://dx.doi.org/10.1016/j.ebiom.2023.104632

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