Table 5.

Performance achieved by the deep learning (DL) models in classifying the pediatric CXR dataset (baseline) into bacterial and viral categories. Here, Acc.: accuracy, Sens.: sensitivity, Prec.: precision, F: F-score, and MCC: Matthews correlation coefficient.

Models	Acc.	AUC	Sens.	Spec.	Prec.	F	MCC
Custom WRN	0.8974	0.9534	0.9381	0.8311	0.9008	0.9191	0.7806
VGG-16	0.9308	0.9565	0.9711	0.8649	0.9216	0.9457	0.8527
Inception-V3	0.9103	0.937	0.9587	0.8311	0.9028	0.9299	0.8085
Xception	0.9282	0.954	0.9546	0.8852	0.9315	0.9429	0.8469
DenseNet-121	0.9026	0.9408	0.967	0.7973	0.8864	0.925	0.7931
NASNet-mobile	0.9282	0.9479	0.9753	0.8514	0.9148	0.944	0.8477

Bold numerical values denote superior performance.