Mitigating bias in machine learning for medicine

Several sources of bias can affect the performance of machine learning systems used in medicine and potentially impact clinical care. Here, we discuss solutions to mitigate bias across the different development steps of machine learning-based systems for medical applications.

Detalles Bibliográficos
Autores principales: Vokinger, Kerstin N., Feuerriegel, Stefan, Kesselheim, Aaron S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Comment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611652/
https://www.ncbi.nlm.nih.gov/pubmed/34522916
http://dx.doi.org/10.1038/s43856-021-00028-w
Descripción
Sumario:Several sources of bias can affect the performance of machine learning systems used in medicine and potentially impact clinical care. Here, we discuss solutions to mitigate bias across the different development steps of machine learning-based systems for medical applications.

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