COVID-19 Detection Using Chest X-Ray Images with Deep Learning and Transfer Learning

Modern medical diagnosis heavily relies on imaging techniques such as CT scans and X-rays, yet there is an increasing shortage of medical imaging specialists. The rapidly advancing field of artificial intelligence (AI) offers the potential for intelligent-assisted diagnosis, significantly improving screening efficiency. Detecting COVID-19 through chest X-ray images has proven to be effective, especially when supported by state-of-the-art AI and computer vision techniques. This study focuses on detecting COVID-19 through X-ray images using deep learning (DL) and transfer learning (TL) methods. The main contributions are twofold: firstly, a comparative analysis of the performance and effects of various DL models, and secondly, the application of transfer learning with fine-tuning techniques to upgrade detection accuracy. This study can be used in practice as an aid for doctors to diagnose COVID-19, providing them with a reference and reducing the rate of misdiagnosis.