A translational perspective towards clinical AI fairness

Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the fairness of such data-driven insights remains a concern in high-stakes fields. Despite extensive developments, issues of AI fairness in clinical contexts have not been adequately addressed. A fair model...

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Detalles Bibliográficos
Autores principales: Liu, Mingxuan, Ning, Yilin, Teixayavong, Salinelat, Mertens, Mayli, Xu, Jie, Ting, Daniel Shu Wei, Cheng, Lionel Tim-Ee, Ong, Jasmine Chiat Ling, Teo, Zhen Ling, Tan, Ting Fang, RaviChandran, Narrendar, Wang, Fei, Celi, Leo Anthony, Ong, Marcus Eng Hock, Liu, Nan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Perspective
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502051/
https://www.ncbi.nlm.nih.gov/pubmed/37709945
http://dx.doi.org/10.1038/s41746-023-00918-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502051/
https://www.ncbi.nlm.nih.gov/pubmed/37709945
http://dx.doi.org/10.1038/s41746-023-00918-4

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