A translational perspective towards clinical AI fairness

A translational perspective towards clinical AI fairness

Abstract 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 fa...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Narrendar RaviChandran, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu
Format: Artykuł
Język:English
Wydane: Nature Portfolio 2023-09-01
Seria:npj Digital Medicine
Dostęp online:https://doi.org/10.1038/s41746-023-00918-4

Internet

https://doi.org/10.1038/s41746-023-00918-4

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