Table 2 Evaluation of machine learning models (Without multimodal radiomics Data).
Accuracy (95% CI) | AUC (95% CI) | Recall (95% CI) | Precision (95% CI) | F1 (95% CI) | F0.5 (95% CI) | F2 (95% CI) | Kappa (95% CI) | MCC (95% CI) | Brier (95% CI) | |
|---|---|---|---|---|---|---|---|---|---|---|
Logistic Regression | 0.62 (0.49,0.75) | 0.62 (0.29,0.39) | 0.25(0.11,0.31) | 0.45 (0.11,0.31) | 0.32 (0.11,0.31) | 0.39 (0.11,0.31) | 0.27 (0.11,0.31) | 0.09 (0.11,0.31) | 0.09 (0.09,0.31) | 0.23 (0.29,0.39) |
KNN | 0.69 (0.58,0.8) | 0.74 (0.32,0.47) | 0.6 (0.25,0.51) | 0.57 (0.25,0.51) | 0.59 (0.25,0.53) | 0.58 (0.25,0.51) | 0.59 (0.25,0.51) | 0.34 (0.25,0.51) | 0.34 (0.25,0.51) | 0.21 (0.32,0.47) |
SVM | 0.64 (0.49,0.75) | 0.61 (0.3,0.39) | 0.4 (0.18,0.42) | 0.5 (0.18,0.42) | 0.44 (0.18,0.42) | 0.48 (0.18,0.42) | 0.42 (0.18,0.42) | 0.18 (0.18,0.42) | 0.18 (0.16,0.42) | 0.23 (0.3,0.39) |
Decision Tree | 0.67 (0.55,0.78) | 0.67 (0.31,0.56) | 0.65 (0.29,0.58) | 0.54 (0.31,0.56) | 0.59 (0.31,0.58) | 0.56 (0.31,0.56) | 0.63 (0.31,0.56) | 0.32 (0.31,0.56) | 0.33 (0.31,0.56) | 0.33 (0.31,0.56) |
Random Forest | 0.75 (0.64,0.85) | 0.77 (0.32,0.42) | 0.55 (0.18,0.4) | 0.69 (0.18,0.4) | 0.61 (0.18,0.42) | 0.65 (0.18,0.42) | 0.57 (0.18,0.42) | 0.43 (0.18,0.4) | 0.43 (0.18,0.4) | 0.18 (0.32,0.43) |
LightGBM | 0.73 (0.6,0.84) | 0.73 (0.23,0.43) | 0.55 (0.18,0.44) | 0.65 (0.2,0.44) | 0.59 (0.18,0.44) | 0.63 (0.18,0.44) | 0.57 (0.18,0.44) | 0.39 (0.2,0.42) | 0.39 (0.2,0.44) | 0.24 (0.23,0.43) |
ExtraTrees | 0.69 (0.58,0.8) | 0.71 (0.29,0.39) | 0.4 (0.13,0.35) | 0.62 (0.13,0.35) | 0.48 (0.13,0.35) | 0.56 (0.13,0.35) | 0.43 (0.13,0.35) | 0.28 (0.13,0.35) | 0.29 (0.13,0.35) | 0.2 (0.29,0.39) |
GradientBoosting | 0.75 (0.64,0.85) | 0.79 (0.16,0.4) | 0.55 (0.18,0.42) | 0.69 (0.18,0.42) | 0.61 (0.18,0.42) | 0.65 (0.18,0.42) | 0.57 (0.18,0.42) | 0.43 (0.18,0.42) | 0.43 (0.18,0.42) | 0.24 (0.18,0.39) |
Gaussian Naive Bayes | 0.67 (0.55,0.8) | 0.68 (0.31,0.45) | 0.65 (0.31,0.56) | 0.54 (0.31,0.56) | 0.59 (0.31,0.56) | 0.56 (0.29,0.55) | 0.63 (0.31,0.56) | 0.32 (0.31,0.58) | 0.33 (0.31,0.58) | 0.22 (0.3,0.45) |
XGBoost | 0.76 (0.64,0.87) | 0.74 (0.23,0.43) | 0.6 (0.2,0.44) | 0.71 (0.18,0.44) | 0.65 (0.18,0.44) | 0.68 (0.18,0.42) | 0.62 (0.2,0.44) | 0.47 (0.2,0.42) | 0.48 (0.2,0.44) | 0.22 (0.23,0.44) |
Stacking Model | 0.73 (0.6,0.84) | 0.76 (0.3,0.41) | 0.55 (0.18,0.44) | 0.65 (0.18,0.44) | 0.59 (0.2,0.42) | 0.63 (0.2,0.42) | 0.57 (0.2,0.44) | 0.39 (0.2,0.44) | 0.39 (0.18,0.44) | 0.19 (0.3,0.41) |
