Algorithmic fairness in pandemic forecasting: lessons from COVID-19

Racial and ethnic minorities have borne a particularly acute burden of the COVID-19 pandemic in the United States. There is a growing awareness from both researchers and public health leaders of the critical need to ensure fairness in forecast results. Without careful and deliberate bias mitigation,...

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Detalles Bibliográficos
Autores principales: Tsai, Thomas C., Arik, Sercan, Jacobson, Benjamin H., Yoon, Jinsung, Yoder, Nate, Sava, Dario, Mitchell, Margaret, Graham, Garth, Pfister, Tomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Perspective
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090910/
https://www.ncbi.nlm.nih.gov/pubmed/35538215
http://dx.doi.org/10.1038/s41746-022-00602-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090910/
https://www.ncbi.nlm.nih.gov/pubmed/35538215
http://dx.doi.org/10.1038/s41746-022-00602-z

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