VG-16 Model-Based Pneumonia Detection with Chest X-Ray Images

Particularly in underdeveloped areas, pneumonia is still a major worldwide health concern that directly affects Sustainable Development Goal (SDG) 3: Good Health and Well-Being of the United Nations. This work employs a fine-tuned VG-16-based convolutional neural network (CNN) that automatically detects pneumonia in chest X-ray (CXR) images based on deep learning. The model obtained 95% accuracy with a precision of 0.94 for “no pneumonia” and 0.95 for “pneumonia” cases from a dataset of 5,863 images. Consistent with SDG 9: Industry, Innovation, and Infrastructure, the research guarantees dependable and open diagnostics. Particularly in areas with limited resources, the model seems to be a practical approach to raising diagnosis skills. Still, there are problems with it, including an unbalanced dataset and limited applicability.