Detecting Pneumonia with Chest X-Ray Using Transfer Learning with ResNet50

Pneumonia is a lung disease caused by infections due to bacteria. Early diagnosis is critical for its proper treatment. In general, a trained radiologist may diagnose the condition using chest X-ray pictures. In the present study, modern deep learning techniques are used to automatically detect pneumonia from chest X-ray pictures. ResNet-50, a pre-trained deep convolutional neural network (CNN) model, is used in combination with transfer learning. This study aims to streamline the diagnostic process while enhancing accuracy. This research demonstrate the efficiency of these techniques in reliably diagnosing pneumonia cases with high precision, recall, and F1-score rates of around 98 percent each. In this study, an impressive test accuracy of 98.66 percent and an area under the curve (AUC) of 98 percent is achieved, demonstrating the effectiveness of proposed approach in reliably detecting the target condition. The achieved accuracy and AUC values validate proposed method's ability to provide accurate and trustworthy predictions, highlighting its potential to improve diagnostic processes.