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. 2020 Oct 2;10:558162. doi: 10.3389/fonc.2020.558162

TABLE 4.

Summary of the subgroup-specific classification performance of the RLHC model.

Molecular subgroups Cohorts Area under the curve ACC (%) SEN (%) SPE (%)
Wingless Training 0.8277 (0.7133–0.9421) 85.87 (53.26–93.48) 66.67 (53.33–100.00) 89.61 (44.16–97.40)
Testing 0.9097 (0.7987–1.0000) 80.00 (70.00–96.67) 83.33 (83.33–100.00)  79.17 (62.50–100.00)
Sonic hedgehog Training 0.8997 (0.8236–0.9758) 90.22 (65.22–95.65) 75.00 (68.75–100.00) 93.42 (57.89–98.68)
Testing 0.8654 (0.6609–1) 86.67 (56.67–100.00) 75.00 (75.00–100.00)  88.46 (50.00–100.00)
Group 3 Training 0.8803 (0.8059–0.9547) 81.52 (76.09–90.22) 87.50 (65.00–97.50) 76.92 (67.31–98.08)
Testing 0.6652 (0.4667–0.8636) 70.00 (60.00–83.33) 100.00 (35.71–100.00)  50.00 (25.00–100.00)
Group 4 Training 0.9202 (0.8372–1.00) 92.39 (82.61–96.74)  76.19 (71.43–100.00)  97.18 (80.28–100.00)
Testing 0.6736 (0.3714–0.9759) 86.67 (50.00–93.33)  33.33 (16.67–100.00) 100.00 (41.67–100.00)

RLHC model means the model combining the 11 selected radiomics features, the tumor location, the hydrocephalus information, and the clinical factors. ACC, SEN, and SPE are short for accuracy, sensitivity and specificity, respectively. The 95% confidence interval for each index is shown.