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• W3131116417 abstract "A virus spread from China to all around the world named COVID-19 has now become a demon. The fear of death can be easily seen in citizens of around 180 countries and fear to force us indoors. This is a demon of the twenty-first century; typically, this demon does not link with any of the evil, occultism, literature, fiction, mythology, and folklore. COVID-19 is a member of the coronavirus family and caused by the SARS-CoV-2 virus. COVID-19 was first identified in December 2019 at Wuhan, China. SARS virus is responsible for respiratory illness known as COVID-19. We have limited articles on COVID-19 with machine learning (ML) and AI. We do not have any antivirus medicine and other dataset that bring in mind about prediction, detection, and stage identification of COVID-19 in human bodies. Therefore, we decided to bring a machine learning-based technique with a list of datasets that will apply to coronavirus dataset for identification. It is believed that ML and artificial intelligence can help accelerate solutions for predicting the stage of infection. Data analysis presented in this paper helps in minimizing the virus impact with all the other research." @default.
• W3131116417 created "2021-03-01" @default.
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• W3131116417 date "2021-01-01" @default.
• W3131116417 modified "2023-09-24" @default.
• W3131116417 title "Machine Learning-Based Scheme to Identify COVID-19 in Human Bodies" @default.
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• W3131116417 doi "https://doi.org/10.1007/978-3-030-60039-6_2" @default.
• W3131116417 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7979240" @default.
• W3131116417 hasPublicationYear "2021" @default.
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