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@article{158721,
        author = {Thopella Pranati and P. Akhil Kumar and Jakka Manasa and K.Shilpa},
        title = {PNEUMONIA & COVID19 DETECTION USING MACHINE & DEEP LEARNING ALGORITHMS},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {10},
        pages = {584-589},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=158721},
        abstract = {The World Health Organization (WHO) identified coronavirus as the 2019 cause of a global pandemic. SARS-CoV-2, otherwise called the serious intense respiratory condition Covid 2, was found in China toward the finish of December 2019 and is liable for Coronavirus. The whole world was impacted inside a couple of months. Because of the way that large number of individuals all over the planet have been tainted with Coronavirus, it has arisen as a worldwide medical problem. More often than not, the infection is infectious, and the individuals who get it can immediately spread it to anybody they come into contact with. Subsequently, observation is an effective method for preventing the infection from deteriorating. Pneumonia is another illness brought on by an infection that is identical to the Coronavirus. The reality of pneumonia can go from minor to perilous. People under the age of 65, children, and those with weaker immune systems are particularly vulnerable to this. In this review, we use a variety of machine learning and deep learningmethods to identify pneumonia caused by the Coronavirus from chest X-rays. Evaluation of execution largely relied on grouping precision},
        keywords = {Deep learning, machine learning, COVID-19, and SARS-CoV-2},
        month = {},
        }