Algorithmic fairness in computational medicine.
Algorithmic fairness in computational medicine.
复制标题
计算医学中的数学公平性。
DOI:
10.1016/j.ebiom.2022.104250
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发表时间:
2022-10
期刊:
影响因子:
11.1
通讯作者:
Wang, Fei
中科院分区:
文献类型:
--
作者:
Xu, Jie;Xiao, Yunyu;Wang, Wendy Hui;Ning, Yue;Shenkman, Elizabeth A.;Bian, Jiang;Wang, Fei
Machine learning models are increasingly adopted for facilitating clinical decision-making. However, recent research has shown that machine learning techniques may result in potential biases when making decisions for people in different subgroups, which can lead to detrimental effects on the health and well-being of specific demographic groups such as vulnerable ethnic minorities. This problem, termed algorithmic bias, has been extensively studied in theoretical machine learning recently. However, the impact of algorithmic bias on medicine and methods to mitigate this bias remain topics of active discussion. This paper presents a comprehensive review of algorithmic fairness in the context of computational medicine, which aims at improving medicine with computational approaches. Specifically, we overview the different types of algorithmic bias, fairness quantification metrics, and bias mitigation methods, and summarize popular software libraries and tools for bias evaluation and mitigation, with the goal of providing reference and insights to researchers and practitioners in computational medicine.
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影响因子:
3.7
作者:
Dawid, AP
通讯作者:
Dawid, AP
影响因子:
7.6
作者:
BARON, J;HERSHEY, JC
通讯作者:
HERSHEY, JC
DOI:
10.1109/tvcg.2020.3030455
发表时间:
2021-02-01
影响因子:
5.2
作者:
Borland, David;Zhang, Jonathan;Gotz, David
通讯作者:
Gotz, David
影响因子:
64.8
作者:
Esteva A;Kuprel B;Novoa RA;Ko J;Swetter SM;Blau HM;Thrun S
通讯作者:
Thrun S
DOI:
10.1056/nejmp1714229
发表时间:
2018-03-15
期刊:
The New England journal of medicine
影响因子:
--
作者:
Char DS;Shah NH;Magnus D
通讯作者:
Magnus D