Who was at risk for COVID-19 late in the US pandemic? Insights from a population health machine learning model

Notable discrepancies in vulnerability to COVID-19 infection have been identified between specific population groups and regions in the USA. The purpose of this study was to estimate the likelihood of COVID-19 infection using a machine-learning algorithm that can be updated continuously based on hea...

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Detalles Bibliográficos
Autores principales: Adeoye, Elijah A., Rozenfeld, Yelena, Beam, Jennifer, Boudreau, Karen, Cox, Emily J., Scanlan, James M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090454/
https://www.ncbi.nlm.nih.gov/pubmed/35538201
http://dx.doi.org/10.1007/s11517-022-02549-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090454/
https://www.ncbi.nlm.nih.gov/pubmed/35538201
http://dx.doi.org/10.1007/s11517-022-02549-5

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