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Table 5 Evaluation results for prostate cancer detection: Feature selection based on Sensitivity and Specificity (Results are shown with 95 % confidence interval)

From: Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

Target Performance evaluation criteria Sensitivity Specificity AUC
Sensitivity Sensitivity 0.86 [0.75 0.97] 0.82 [0.78 0.87] 0.86 [0.81 0.91]
Specificity Specificity 0.80 [0.69 0.91] 0.88 [0.85 0.92] 0.88 [0.83 0.93]
AUC Specificity 0.84 [0.76 0.91] 0.86 [0.82 0.91] 0.90 [0.88 0.93]