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@article{156544,
        author = {Abrar Rashid and Yogesh},
        title = {An automated COVID analysis using Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {3},
        pages = {850-855},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156544},
        abstract = {Advancements in technology has put a rapid and huge impact on every field of life, be it defence, commerce, medical or any other field. Artificial intelligence has exhibited affirmative results in health care industry through its decision-making capability by analysing the data. More than 100 countries got affected by COVID-19 during a matter of no time. In the coming future, people are highly vulnerable to its incoming consequences. It is crucial to find out and develop a control system which will help in detecting the corona virus. To control the current mayhem, one of the solutions can be to use various AI tools in the diagnosis of this disease. According to a clinical study of COVID-19 infected patients, it was depicted that these patients, after coming in contact with this virus, are highly infected from a lung infection. The more efficient imaging techniques for detecting lungs related problems are chest x-ray (i.e., radiography) and chest CT. A chest x-ray is considerably a lower cost process in comparison to a chest CT. One of the most efficacious technique of machine learning is considered to be deep learning. It provides numerous beneficial analysis to study a very large number of images of chest x-rays which can have crucial effect on screening of Covid-19. In this work, we have taken into consideration the chest x-ray and CT scans of healthy patients as well as covid-19 affected patients and then trained our model to produce the results for the detection of virus.},
        keywords = {Covid-19, X-Ray, CT scan. Deep Learning, Convolution neural network.},
        month = {},
        }