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Table 5 Comparison of ROC analysis results

From: Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI

IHC status AUROC Z statistic p value
ER(+) VS. ER(−) Histogram VS. Texture 4.531 < 0.001
Histogram VS. GLCM 0.462 0.644
Histogram VS. RLM 0.312 0.7548
Texture VS. GLCM −4.147 < 0.001
Texture VS. RLM −4.322 < 0.001
GLCM VS. RLM −0.171 0.864
PR(+) VS. PR(−) Histogram VS. Texture 3.676 < 0.001
Histogram VS. GLCM −0.412 0.680
Histogram VS. RLM 0.058 0.954
Texture VS. GLCM −3.941 < 0.001
Texture VS. RLM −3.607 < 0.001
GLCM VS. RLM 0.462 0.644
HER2(+) VS. HER2(−) Histogram VS. Texture 3.189 0.001
Histogram VS. GLCM −0.236 0.814
Histogram VS. RLM −2.267 0.023
Texture VS. GLCM −3.407 < 0.001
Texture VS. RLM −4.918 < 0.001
GLCM VS. RLM −2.099 0.036
Ki-67 low VS. high Histogram VS. Texture 3.493 < 0.001
Histogram VS. GLCM −1.542 0.123
Histogram VS. RLM −0.559 0.576
Texture VS. GLCM −4.795 < 0.001
Texture VS. RLM −4.066 < 0.001
GLCM VS. RLM 1.174 0.240
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