The COVID-19 pandemic, caused by SARS-CoV-2, originated in December 2019 and spread rapidly around the world, with about 600 million verified cases reported by October 2022. It causes a global lockdown as well as several challenges and issues which affect everyone across the world. Accurate COVID-19 disease detection and diagnosis are crucial for those who report symptoms. A big challenge in controlling this pandemic is its timely detection and timely provision of proper healthcare facilities to patients.

This research evaluates the application of artificial intelligence (AI) technology to assist in the timely identification of COVID-19 disease by examining chest X-ray images. The main objective of the proposed research is to explore the effectiveness of the ResNet-50 Deep Learning Algorithm in COVID-19 detection from chest X-ray images. An adequate dataset was created by gathering chest X-ray images from different research papers and other sources to make this research more effective and easier. The proposed dataset comprises 7232 images, including 3616 COVID-19 images and the remaining 3616 normal images. Deep Learning is flexible and commonly employed in numerous fields, especially in the medical field. Its capability to detect intricate patterns, similar to human imagination, is what defines it as highly valuable. In this research deep learning models especially Resnet-50 along with other pertained models were implemented to get precise results. The proposed model attained a strong performance with 97% accuracy, 96% precision, and 97% recall on the test set, showing its effectiveness in distinguishing between COVID-19 and normal chest X-rays.

Index Terms- Chest X-Rays, ResNet-50 Model, Detection of COVID-19, Deep Learning Models.