| Training set | AUC | Sensitivity | Specificity | Accuracy | PPV | NPV | Semantic model | 0.902 [86.3, 94.1] | 0.756 [66.3, 84.9] | 0.933 [88.2, 98.5] | 0.849 [79.5, 90.2] | 0.912 [84.4, 97.9] | 0.808 [73.2, 88.3] | Multiparametric model | 0.89 [85.1, 92.9] | 0.793 [70.5, 88.0] | 0.844 [77.0, 91.9] | 0.820 [76.2, 87.7] | 0.823 [73.9, 90.7] | 0.817 [73.9, 89.6] | Combined radiomics and semantic model | 0.924 [88.5, 96.3] | 0.866 [79.2, 94.0] | 0.844 [77.0, 91.9] | 0.855 [80.2, 90.7] | 0.835 [75.6, 91.4] | 0.874 [80.4, 94.3] |
| Test set | AUC | Sensitivity | Specificity | Accuracy | PPV | NPV | Semantic model | 0.823 [70.5, 94.1] | 0.783 [61.4, 95.1] | 0.850 [69.4, 100.0] | 0.814 [69.8, 93.0] | 0.857 [70.7, 100.0] | 0.773 [59.8, 94.8] | Multiparametric model | 0.792 [67.4, 91.0] | 0.522 [31.8, 72.6] | 0.900 [76.9, 100.0] | 0.698 [56.0, 83.5] | 0.857 [67.4, 100.0] | 0.621 [44.4, 79.7] | Combined radiomics and semantic model | 0.848 [75.0, 94.6] | 0.739 [56.0, 91.9] | 0.800 [62.5, 97.5] | 0.767 [64.1, 89.4] | 0.810 [64.2, 97.7] | 0.727 [54.1, 91.3] |
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