Radiological Analysis with CNN for Respiratory Diseases

The need for swift and precise diagnostics in respiratory illnesses like COVID-19 and Pneumonia has increased in recent years. Deep Learning has been increasingly used in research and development of tools on disease diagnosis in the recent years. This research paper introduces an automated system developed through deep learning methodologies for the radiological analysis for the detection of Pneumonia and Covid-19. Employing pre-trained CNN models-including MobileNet, InceptionV3, and ResNet50-this study harnesses their advanced image processing capabilities to effectively discern and classify COVID-19 and Pneumonia from chest radiographs. This enhancement not only aids healthcare practitioners in expediting diagnostic determinations but also amplifies the accessibility of diagnostic tools, particularly in resource-limited settings. Preliminary findings from the analysis of these models, they demonstrate commendable levels of accuracy and reliability, highlighting their potential as indispensable assets in combating respiratory ailments.