Improving Diagnosis Accuracy With An Intelligent Image Retrieval System For Lung Pathologies Detection: A Features Extractor Approach

This article discusses the potential of deep learning in revolutionizing the detection and diagnosis of lung pathologies. It introduces a tailored computer-assisted system designed for the automatic retrieval of annotated medical images that share similar content. The system is based on a fusion of YOLOv5 and EfficientNet within the features extractor module. Through rigorous experimentation conducted on an extensive and diverse dataset, the proposed solution decisively surpasses conventional methodologies.