Figure 2.

ROC curves for CNN-LSTM deep learning models with a different set of sequences for prediction of PsP from TP. Each ROC curve for each modality obtained from threefold cross-validation (CV1, CV2, and CV3). The x-axis is the true negative rate (TNR) or specificity and the y-axis is true positive rate (TPR) or sensitivity. The mean AUC, area under ROC curve, values were (a) 0.64 for a set of 3 modalities, (b) 0.69 for a set of 5 modalities, and (c) 0.81 for a set of 7 modalities.