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

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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Bibliographic Details
Main Authors: Bakr Ahmed Taha, Yousif Al Mashhadany, Abdulmajeed H. J. Al-Jumaily, Mohd Saiful Dzulkefly Bin Zan, Norhana Arsad
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Viruses
Subjects:
SARS-CoV-2
artificial intelligence
RNN
morphometry
transmission electron microscopy
Online Access:https://www.mdpi.com/1999-4915/14/11/2386

Internet

https://www.mdpi.com/1999-4915/14/11/2386

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