Fig. 2

Performance of TabNet on the hold-out test set. A Comparison of the ROC curves of TabNet with the other baseline models. TabNet outperformed all the trained baseline models as mirrored by the area under the ROC curves (AUC). B Confusion matrix of TabNet for CD73 classification. LR, Logistic Regression; RF, Random Forest; SVM, Support Vector Machine; TabNet, Attentive Interpretable Tabular Learning; XGBoost, Extreme Gradient Boosting