Table 4.
Comparative performance indices of prediction models when using 34 new validation datasets to predict pathological complete response.
| Sensitivity | 1-Specificity | PPV | NPV | Accuracy | AUROC | |
|---|---|---|---|---|---|---|
| ANN | 0.94 | 0.80 | 0.89 | 0.87 | 0.88 | 0.84 |
| KNN | 0.80 | 0.67 | 0.87 | 0.60 | 0.80 | 0.74 |
| SVM | 0.91 | 0.76 | 0.86 | 0.72 | 0.71 | 0.76 |
| NBC | 0.90 | 0.53 | 0.79 | 0.84 | 0.80 | 0.63 |
| MLR | 0.88 | 0.79 | 0.84 | 0.49 | 0.83 | 0.77 |
ANN artificial neural network, KNN K nearest neighbor, SVM support vector machines, NBC Naive Bayes classifier, MLR multiple logistic regression, PPV positive predictive value, NPV negative predictive value, AUROC area under the receiver operating characteristic.