医学
无线电技术
射线照相术
风险评估
梅德林
放射科
深度学习
人工智能
医学物理学
计算机安全
计算机科学
政治学
法学
作者
Hadiseh Kavandi,Pranav Kulkarni,Sean P. Garin,Preetham Bachina,Vishwa S. Parekh,Paul H. Yi
出处
期刊:American Journal of Roentgenology
[American Roentgen Ray Society]
日期:2024-10-16
摘要
Using two public CXR datasets, radiomics ML models showed moderate-to-good performance for predicting patients’ age, sex, and self-reported race. This encoding of demographic characteristics by radiomics ML models raises concern for biases similar to those previously identified for deep-learning models, requiring radiologist vigilance and further study.
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