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Table 2 Performance Evaluation of Known Confounders

From: Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA

Confounder k-fold CV AUC (95% CI) k-fold CV Sensitivity at 85% Specificity (95% CI) Confounder CV method Confounder CV AUC (95% CI)
Age 0.71 (0.64–0.77) 44% (29–57%) Binned-age 0.50 (0.50–0.50)
Batch 0.72 (0.69–0.75) 43% (31–53%) k-batch 0.50 (0.50–0.50)
Processing Date 0.69 (0.64–0.74) 38% (25–49%) Ordered k-batch 0.48 (0.43–0.52)
Institution 0.87 (0.84–0.90) 74% (72–77%) Balanced k-batch 0.51 (0.28–0.74)
  1. Performance evaluation of known confounders alone to predict cancer with either k-fold or the CV procedure designed to control for the confounder. Confidence intervals are calculated from bootstrapped distributions of the metric across folds