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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]