Algorithmic fairness in pandemic forecasting: lessons from COVID-19

Algorithmic fairness in pandemic forecasting: lessons from COVID-19

Abstract 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 mi...

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Bibliographic Details
Main Authors: Thomas C. Tsai, Sercan Arik, Benjamin H. Jacobson, Jinsung Yoon, Nate Yoder, Dario Sava, Margaret Mitchell, Garth Graham, Tomas Pfister
Format: Article
Language:English
Published: Nature Portfolio 2022-05-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-022-00602-z

Internet

https://doi.org/10.1038/s41746-022-00602-z

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