Pneumonia Detection using Chest X-Ray Images and Machine Learning Techniques

Abstract

Abstract— Chest X-rays have been a crucial diagnostic tool in detecting pneumonia. The disease manifests as inflammation and filling of the air spaces within the lungs, leading to changes in the appearance of the lungs on X-rays. In recent times, advances in computer vision and machine learning have allowed for the development of automated systems for pneumonia detection using chest X-rays. These systems leverage deep learning techniques to analyze X-ray images and identify patterns associated with pneumonia. The use of these systems can aid in early diagnosis and prompt treatment, potentially leading to improved patient outcomes. Despite their promise, there are still challenges to be addressed, including the need for large and diverse datasets for training and the need for further validation of these systems in real-world settings. Nevertheless, the development of automated pneumonia detection systems using chest X-rays has the potential to revolutionize the field of radiology and improve patient care. Index Terms—Pneumonia; artificial intelligence; machine learning; image processing; convolutional neural network; chest x-rays.