Enhancing Pneumonia Detection from Chest X-ray Images Using Convolutional Neural Network and Transfer Learning Techniques

Pneumonia is a serious lung disease caused by a variety of viruses. Chest X-rays may be difficult to use to diagnose and treat pneumonia as it may be difficult to distinguish it from other respiratory disorders. A specialist must review chest X-ray pictures in order to diagnose pneumonia. The process is time-consuming and imprecise. This study aims to simplify the process of diagnosing pneumonia from chest X-ray pictures through the use of CNN-based computer-aided classification methods. One of the key problems with the CNN model is that it requires a lot of data to be accurate. As we began, our dataset was limited, so the model had a reduced accuracy rate. To overcome this issue, we used transfer learning with the VGG19 model, which led to a significant improvement in accuracy, reaching 90% throughout testing.