Abstract

Pneumonia, a potentially fatal lung disease caused by viral or bacterial infection, poses challenges in diagnosis from chest X-ray images due to similarities with other lung infections. This research aims to develop a computer-aided system for pneumonia detection in children, enhancing diagnostic accuracy. In this paper, five established deep learning models such as VGG-16, VGG-19, ResNet-50, Inception-V3, Xception pre-trained on ImageNet have been used. These models have been applied on the chest X-ray dataset to optimize performance. Xception provides recall, specificity, accuracy and AUC of 97.43%, 91.02%, 95.06% and 94.23%, respectively.

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