Machine Learning Method: A Better Approach For İdentifying COVID-19 Patients

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Shivani Dubey, Adnan Ahmad, Anurag Srivastava, Ravi Sharma


Recently, the last year has been very difficult for the entire world and the cause is COVID-19, an infectious disease caused by a family of virus known as corona virus. This disease has been declared as a world-wide pandemic by the World Health Organization (WHO) in March 2020.These viruses cause severe respiratory problems, ranging from common cold to deaths of patients due to Severe Acute Respiratory Syndrome (SARS). Even after the vaccines have been discovered, successful detection of COVID-19 in a patient still needs improvement.  Through this paper, we shall discuss various existing methods and approaches used in the identification of COVID-19 virus. Moreover, we shall discuss about the various datasets that are required for carrying out the detection and at last a comparing these methods on parameters to know which method has the best accuracy rates.

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