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Table 3 The performance of the two models on the training set and our final selected model on the test set, evaluated using area under the curve (AUC), specificity and, sensitivity

From: Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions

  LOPO CV Independent Testing
Ensemble Model Penalized Logistic Model Penalized Logistic Model
Sample-level In silico mixing Sample-level In silico mixing In vitro mixing
AUC 0.90
[0.87–0.93]
0.93
[0.88–0.98]
0.87
[0.83–0.91]
0.91
[0.85–0.97]
0.87
[0.76–0.98]
Specificity 0.92
[0.86–0.96]
0.95
[0.82–0.99]
0.91
[0.85–0.95]
0.95
[0.82–0.99]
0.88
[0.70–0.98]
Sensitivity 0.73
[0.67–0.79]
0.79
[0.66–0.89]
0.71
[0.64–0.77]
0.72
[0.58–0.83]
0.70
[0.47–0.87]