A Comparative Analysis of Pneumonia Detection Using Chest X-rays with DNN

A variety of viral infections can develop in pneumonia–known to be highly catastrophic lung disease. Due to the close association between pneumonia and other lung disorders, the diagnosis of pneumonia using chest X-ray images presents a significant challenge. Due to this issue, higher levels of accuracy cannot be gained from the recent approaches for detecting pneumonia. In this research, pneumonia is classified using deep learning algorithms. CNN model was developed to make chest X-ray diagnosis easier. Furthermore, the utilization of pre-trained convolutional neural network (CNN) models, which extract features from vast datasets, proves highly advantageous in the branch of image classification applications. In our analysis, we use a selection process to determine the most suitable CNN model for the task at hand. CNN models offer substantial assistance in the evaluation of chest X-ray images, particularly in the identification of pneumonia. To effectively identify pneumonic lungs in chest X-rays and contribute to pneumonia treatment, this article presents a range of convolutional neural network models.