Can we reliably automate clinical prognostic modelling? A retrospective cohort study for ICU triage prediction of in-hospital mortality of COVID-19 patients in the Netherlands

BACKGROUND: Building Machine Learning (ML) models in healthcare may suffer from time-consuming and potentially biased pre-selection of predictors by hand that can result in limited or trivial selection of suitable models. We aimed to assess the predictive performance of automating the process of bui...

Descripción completa

Detalles Bibliográficos
Autores principales: Vagliano, I., Brinkman, S., Abu-Hanna, A., Arbous, M.S, Dongelmans, D.A., Elbers, P.W.G., de Lange, D.W., van der Schaar, M., de Keizer, N.F., Schut, M.C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8791240/
https://www.ncbi.nlm.nih.gov/pubmed/35114522
http://dx.doi.org/10.1016/j.ijmedinf.2022.104688

Ejemplares similares

Ejemplares similares