Pneumonia Disease Analysis Using Deep Learning on X-Ray Images

Pneumonia is a severe lung infection that can be fatal if not detected early. This study aims to develop an effective deep-learning model for detecting pneumonia from chest X-ray images by 5,863 Paul Mooney's images from the Kaggle dataset; this research implements three deep-learning architectures: a basic Convolutional Neural Network (CNN), VGG16, and ResNet50V2. The model development process includes data preprocessing, image augmentation, and transfer learning techniques. Results show significant performance improvement, with the basic CNN model initially achieving 80.60% accuracy and the combined ResNet50V2 model reaching 92.03% accuracy. Analysis using a confusion matrix on the best model produced 93.30% precision, 94.0% recall, and 93.64% F1-score. This study contributes to the development of AI-based pneumonia diagnostic tools, potentially improving the accuracy and speed of disease detection in clinical practice.