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Table 4 Evaluation results for prostate cancer detection: Feature selection based on specificity (results are shown with 95 % confidence interval)

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

Imaging Number of Sensitivity Specificity Accuracy AUC
modality features     
T2w 10 0.66 [0.50 0.81] 0.47 [0.42 0.53] 0.48 [0.43 0.53] 0.57 [0.48 0.66]
CHB-DWI 10 0.69 [0.52 0.86] 0.82 [0.75 0.88] 0.81 [0.75 0.87] 0.76 [0.68 0.84]
ADC 96 0.73 [0.60 0.85] 0.62 [0.55 0.70] 0.63 [0.56 0.71] 0.70. [0.64 0.76]
CDI 10 0.82 [0.69 0.94] 0.85 [0.80 0.89] 0.84 [0.80 0.88] 0.84 [0.78 0.89]
TFM 1= T2w+ADC 110 0.72 [0.59 0.86] 0.63 [0.55 0.70] 0.64 [0.56 0.71] 0.69 [0.63 0.75]
TFM 2=T2w+ADC 40 0.66 [0.50 0.82] 0.77 [0.71 0.83] 0.77 [0.71 0.82] 0.73 [0.65 0.81]
+CHB-DWI      
TFM 3=T2w+CDI 20 0.78 [0.65 0.91] 0.86 [0.82 0.90] 0.86 [0.82 0.89] 0.84 [0.78 0.90]
TFM 4=T2w+ADC+CDI 40 0.77 [0.63 0.90] 0.86 [0.82 0.90] 0.85 [0.81 0.89] 0.84 [0.79 0.89]
TFM 5=T2w+ADC 50 0.78 [0.64 0.91] 0.86 [0.82 0.90] 0.85 [0.82 0.89] 0.84 [0.78 0.90]
+CHB-DWI+CDI      
TFM 6=T2w+ADC 130 0.80 [0.69 0.91] 0.88 [0.85 0.92] 0.88 [0.84 0.91] 0.88 [0.83 0.93]
+CHB-DWI+CDI      
+ b1 + b2 + b3 + b4