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Table 1 Performance measures for selected serum models predicting cancer status

From: Cheminformatics approach to exploring and modeling trait-associated metabolite profiles

  ADC1 (training) LOOCV ADC2 (test) external validation
Accuracy (%) Sensitivity (%) Specificity (%) AUC Accuracy (%) Sensitivity (%) Specificity (%) AUC
Single metabolite classifiers
 Aspartic Acid 62.5 40.8 96.8 0.698 79.1 62.8 95.3 0.862
 Cystine 70.0* 75.5 61.3 0.685 55.8* 76.7 34.9 0.677
 Glutamic Acid 62.5 42.9 93.5 0.687 76.7 65.1 88.4 0.846
 Oxalic Acid 70.0* 83.7 48.4 0.65 57.0* 88.4 25.6 0.649
Multi-metabolite classifiers—clustered metabolites
 Cluster 1a SVMb 76.3* 77.6 74.2 0.751 84.9* 72.1 97.7 0.856
  1. Asterisk represents best model accuracies according to LOOCV. Best model accuracies according to external validation accuracy are underlined
  2. aAspartic acid, cystine, glutamic acid
  3. bSupport vector machines