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Table 1: Various test metrics for binary classification. Performance reflects mean of 5 separate seeded runs
Binary Classification Accuracy Sensitivity Specificity PPV NPV ROC AUC
1 section, random initialization 92.83% (1.16%) 89.76% (2.11%) 95.87% (0.43%) 95.61% (0.68%) 90.34% (1.69%) 0.9735 (0.0095)
1 section, pretrained 93.41% (1.13%) 91.07% (2.39%) 95.69% (0.72%) 95.55% (0.46%) 91.48% (2.00%) 0.9815 (0.0059)
3 sections, random initialization 92.40% (0.86%) 90.24% (1.05%) 94.56% (0.92%) 94.32% (1.17%) 90.59% (0.82%) 0.9782 (0.0072)
3 sections, pretrained 93.88% (0.78%) 91.52% (1.40%) 96.23% (0.94%) 96.14% (0.64%) 91.80% (1.71%) 0.9850 (0.0044)
9 sections, random initialization 93.14% (0.95%) 90.79% (2.19%) 95.39% (1.77%) 95.26% (1.81%) 91.28% (1.12%) 0.9821 (0.0064)
9 sections, pretrained 93.14% (0.69%) 91.75% (1.77%) 94.43% (1.85%) 94.43% (1.62%) 92.01% (1.18%) 0.9843 (0.0038)
27 sections, random initialization 93.84% (1.04%) 92.23% (1.88%) 95.40% (1.54%) 95.31% (1.48%) 92.49% (1.46%) 0.9831 (0.0062)
27 sections, pretrained 93.45% (0.64%) 90.67% (1.58%) 96.17% (1.19%) 96.01% (1.15%) 91.17% (0.86%) 0.9858 (0.0041)
The numbers in parentheses represent SD.