Exposure measurement error in air pollution studies: A framework for assessing shared, multiplicative measurement error in ensemble learning estimates of nitrogen oxides

BACKGROUND: Increasingly ensemble learning-based spatiotemporal models are being used to estimate residential air pollution exposures in epidemiological studies. While these machine learning models typically have improved performance, they suffer from exposure measurement error that is inherent in a...

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Detalles Bibliográficos
Autores principales: Girguis, Mariam S., Li, Lianfa, Lurmann, Fred, Wu, Jun, Urman, Robert, Rappaport, Edward, Breton, Carrie, Gilliland, Frank, Stram, Daniel, Habre, Rima
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499078/
https://www.ncbi.nlm.nih.gov/pubmed/30711654
http://dx.doi.org/10.1016/j.envint.2018.12.025

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499078/
https://www.ncbi.nlm.nih.gov/pubmed/30711654
http://dx.doi.org/10.1016/j.envint.2018.12.025

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