Fig. 1. DeepBreath ROC curve for binary classifiers on internal and external validation data.

Each panel shows the ROC curves of one binary classifier: a Control, b Pneumonia, c Wheezing Disorder, d Bronchiolitis. Every iteration of nested CV yields a different model, which produces a receiver-operating characteristic (ROC) curve for the internal test fold. The mean was computed over the obtained ROC curves. For the external validation data, predictions are averaged across the nested CV models, and a single ROC curve is computed. Internal validation is performed on various test folds from the Geneva and Porto Alegre data (blue). External validation (green) is performed on independently collected unseen data from Dakar, Marrakesh, Rabat and Yaoundé.