Limiting bias in AI models for improved and equitable cancer care

被引：1
|
作者：
Ghassemi, Marzyeh [1 ,2 ]
Gusev, Alexander [3 ,4 ]
机构：
[1] MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA
[2] MIT, Inst Med Engn & Sci, Cambridge, MA 02139 USA
[3] Dana Farber Canc Inst, Dept Med Oncol, Boston, MA USA
[4] Harvard Med Sch, Boston, MA USA
来源：
NATURE REVIEWS CANCER | 2024年 / 24卷 / 12期
关键词：
D O I：
10.1038/s41568-024-00739-x
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
Cancer screening, diagnosis and care stand to benefit greatly from advances in artificial intelligence (AI). Researchers, developers and deployers must ensure that applications of AI avoid known racial and gender biases to advance health care for all. Cancer screening, diagnosis and care can benefit greatly from advances in artificial intelligence (AI). In this Comment, Ghassemi and Gusev discuss how AI applications must address and avoid known racial and gender biases to improve health care for all.
引用
收藏
页码：823 / 824
页数：2
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