Table 3.
Elastic-net Regression-LR (%) |
XGBoost - XGB (%) |
Random Forest - RF (%) |
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ACC (SE) | AUC (SE) | SEN (SE) | SP (SE) | ACC (SE) | AUC (SE) | SEN (SE) | SP (SE) | ACC (SE) | AUC (SE) | SEN (SE) | SP (SE) | |
Model 1 outputs | 72 (0.070) | 73 (0.083) | 78 (0.098) | 68 (0.099) | 65 (0.075) | 71 (0.086) | 67 (0.111) | 64 (0.102) | 65 (0.075) | 71 (0.084) | 67 (0.111) | 64 (0.102) |
Model 2 outputs | 92 (0.041) | 95 (0.025) | 94 (0.054) | 91 (0.061) | 90 (0.047) | 92 (0.03) | 89 (0.074) | 91 (0.061) | 90 (0.047) | 92 (0.039) | 89 (0.074) | 91 (0.061) |
Patient info | 88 (0.052) | 96 (0.020) | 72 (0.105) | 100 (0) | 95 (0.034) | 99 (0.006) | 94 (0.054) | 95 (0.044) | 95 (0.034) | 98 (0.01) | 89 (0.074) | 1 (0) |
Model 1 & 2 outputs | 80 (0.063) | 89 (0.054) | 83 (0.087) | 77 (0.089) | 80 (0.063) | 88 (0.053) | 78 (0.098) | 82 (0.082) | 82 (0.060) | 89 (0.054) | 78 (0.09) | 86 (0.073) |
Model 1 outputs + patient info | 78 (0.066) | 86 (0.061) | 78 (0.09) | 77 (0.089) | 65 (0.075) | 79 (0.071) | 72 (0.106) | 59 (0.104) | 75 (0.068) | 85 (0.065) | 72 (0.105) | 77 (0.089) |
Model 2 outputs + patient info | 90 (0.047) | 96 (0.019) | 89 (0.074) | 91 (0.061) | 88 (0.052) | 93 (0.034) | 83 (0.088) | 91 (0.061) | 88 (0.052) | 96 (0.021) | 83 (0.087) | 91 (0.061) |
All | 88 (0.052) | 92 (0.039) | 83 (0.087) | 91 (0.061) | 78 (0.066) | 87 (0.058) | 72 (0.106) | 82 (0.082) | 80 (0.063) | 90 (0.049) | 72 (0.105) | 86 (0.073) |
*ACC-accuracy; AUC area under curve; SEN-sensitivity; SP-specificity; SE-standard error.