PNEUMONIA DETECTION USING CHEST RADIOGRAPHS

AbstractPneumonia is Millions are afflicted by a possibly fatal respiratory virus. globally each year. It may betriggered by several pathogens, such as viruses, fungus, and bacteria, leading to inflammation in thelungs and difficulty in breathing. Since prompt intervention can dramatically lower the disease'smorbidity and mortality, early and accurate diagnosis is necessary for effective therapy and improvedpatient results.In this study, we leverage advanced Using deep learning to identify pneumonia in chest X-ray picturesmodels, a common diagnostic tool used in clinical settings. Specifically, we employed severalprominent architectures, including Convolutional Neural Networks (CNN), Xception, andInceptionResNetV2, ResNet50, Both EfficientNetV2L and VGG16. Due to their demonstratedefficacy in picture classification tasks, these models were selected. particularly in the medical imagingdomain. Keywords: Using X-ray images offers a non-invasive and reasonably priced way to examine lungdiseases.