Published Paper Details:

The worldwide state of health is continuing to be severely impacted by the Covid-19 pandemic. Covid-19 has affected the human race in all aspects of life whether it be mentally, physically, socially, or economically. Diagnosing Covid-19 is a critical task, especially when there is a shortage of resources. Moreover, the present tests and techniques lack solutions to problems such as ease of accessibility, the requirement of rapid response, the cost of testing, the accuracy of results, etc. The most modern Machine Learning (ML) algorithms could be employed to develop a solution that allows for rapid testing and more accurate findings. The model prepared will be a more efficient imaging method to diagnose lungs related problems. Recognizing conceivable corona virus diseases using X-ray of chest will potentially be helpful to isolate patients lies in danger zone. X-ray machines are currently available in most healthcare systems also there is no transportation time needed for the models by a similar token. The timely detection of Severe Acute Respiratory Syndrome CoV-2 (SARS CoV-2), which is the main reason for Wuhan virus, utilizing chest X-ray pictures will prove to be life-saving for both patients and specialists [1]. In the present work, our aim to develop a system that detect of Covid-19 using X-ray images of the chest with the help of the Convolutional Neural Network (CNN) based ML technique. On performing comparative analysis with other models we found CNN to be the appropriate one for our work.