SARS-CoV-2 Morphometry Analysis and Prediction of Real Virus Levels Based on Full Recurrent Neural Network Using TEM Images

The SARS-CoV-2 virus is responsible for the rapid global spread of the COVID-19 disease. As a result, it is critical to understand and collect primary data on the virus, infection epidemiology, and treatment. Despite the speed with which the virus was detected, studies of its cell biology and archit...

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Detalles Bibliográficos
Autores principales: Taha, Bakr Ahmed, Mashhadany, Yousif Al, Al-Jumaily, Abdulmajeed H. J., Zan, Mohd Saiful Dzulkefly Bin, Arsad, Norhana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698148/
https://www.ncbi.nlm.nih.gov/pubmed/36366485
http://dx.doi.org/10.3390/v14112386

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698148/
https://www.ncbi.nlm.nih.gov/pubmed/36366485
http://dx.doi.org/10.3390/v14112386

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