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• W3121645793 abstract "With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided." @default.
• W3121645793 created "2021-02-01" @default.
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• W3121645793 date "2021-01-27" @default.
• W3121645793 modified "2023-10-02" @default.
• W3121645793 title "Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions" @default.
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• W3121645793 doi "https://doi.org/10.3390/ijerph18031117" @default.
• W3121645793 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7908539" @default.
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