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Updated: Feb 11, 2026

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在基于人工智能的质母细胞瘤响应评估算法中评估社会人口统计学偏差

Rachel S Lee1, Dominic LaBella2, Jikai Zhang2

  • 1From the Duke University School of Medicine (R.S.L.); Department of Radiation Oncology (D.L.B.), Department of Radiology (K.M., E.C.), Duke University Medical Center; Department of Electrical and Computer Engineering (J.Z.), Duke University. Rachel.lee@duke.edu.

AJNR. American journal of neuroradiology
|February 9, 2026
PubMed
概括

用于质母细胞瘤细分的AI模型显示出较低的人口偏差. 在多样化的数据集上训练的模型,如BraTS模型,表现更好,比在均数据上训练的模型更少的偏差.

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