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Table 2 1000-times Bootstrap estimate of the area under the ROC curve and the model optimism estimation for the radiomics and CT sign models

From: CT-based radiomics combined with signs: a valuable tool to help radiologist discriminate COVID-19 and influenza pneumonia

Model Apparent AUCa AUC Bootstrap-Trainb (mean, 95% CI) AUC Bootstrap-Testc (mean, 95% CI) Average optimismd Optimism-corrected AUCe
Radiomics 0.888 0.899 (0.897–0.901) 0.838 (0.835–0.841) 0.061 0.827
CT sign 0.906 0.908 (0.907–0.910) 0.888 (0.886–0.890) 0.020 0.886
  1. aThe AUC of predicting model developed in original whole dataset
  2. bThe averaged model performance in the resampled training set after 1000-times bootstrap
  3. cThe averaged model performance in the r “out-of-bag” test set after 1000-times bootstrap
  4. dThe model’s averaged optimism as the difference between the bootstrap training set AUC and the test AUC
  5. eThe corrected AUC by subtracting the average optimism from the apparent AUC