Table 2.
Tabulated content of recurrence with relevant classifier algorithm and corresponding AUC with Kappa values.
| Output | Features | Model | Metric | AUC | Kappa |
|---|---|---|---|---|---|
| Recurrence | Radiomics | pcaNNet (Neural Networks with Feature Extraction) |
Kappa + AUC | 0.77 | 0.53 |
| Radiomics + ADC1 + ADC2 + Change ADC | svmLinearWeights (Linear Support Vector Machines with Class Weights) |
Kappa + AUC | 0.76 | 0.49 | |
| Radiomics + ADC1 | Monmlp (Monotone Multi-Layer Perceptron Neural Network) |
Kappa + AUC | 0.8 | 0.55 | |
| Radiomics + change ADC | RRFglobal (Regularized Random Forest) |
Kappa | 0.74 | 0.5 | |
| Radiomics + change ADC | svmLinearWeights (Linear Support Vector Machines with Class Weights) |
AUC | 0.77 | 0.48 | |
| ADC | FRBCS.W (Fuzzy Rules with Weight Factor) |
Kappa + AUC | 0.57 | 0.17 |