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- W3213888313 abstract "Recently, the coronavirus 2019 or COVID-19, which originated in China, has spread to other countries' population. It is critical to evaluate an automated detection system for rapid alternative prediction and diagnosis in order to reduce the impact of COVID-19. Because of the constant increase in cases, there are fewer COVID-19 available kits than are required for testing in hospitals. Deep learning methods are evolving to provide outstanding performance in the medical field. Deep learning inspired by brain structure is referred to as machine learning. This paper provides an overview of COVID-19’s detection applications based on deep learning. Furthermore, a comprehensive review of the literature on deep leaning in COVID-19 disease has been illustrated. The proposed research study shows that in spite of presence of issues in medical database, where the transfer method can be used effectively." @default.
- W3213888313 created "2021-11-22" @default.
- W3213888313 creator A5080877367 @default.
- W3213888313 date "2021-10-07" @default.
- W3213888313 modified "2023-10-14" @default.
- W3213888313 title "An Overview on Deep Leaning Application in Coronavirus (COVID-19):Diagnosis, Prediction and Effects" @default.
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- W3213888313 doi "https://doi.org/10.1109/icosec51865.2021.9591921" @default.
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