An Overview Of The Artificial Neural Network-Based Applications And Impact Assessment in Covid-19
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021
; 107:1475-1485, 2022.
Article
in English
| Scopus | ID: covidwho-1874753
ABSTRACT
The article is regarding infectious disease which has been affecting people all around the world since December 2019. Write-up gives a brief introduction of the coronavirus from its emergence to the final solution of its exit. It gives us a glimpse of the biological structure of the virus, precautions to be taken in care to reduce the spread of the disease. The description shows us the consequences of the virus-like the mortality rate and the life expectancy rate. The article also presents a few vaccines development projects as a whole to fight COVID-19. It also describes the efficacy of vaccination and the post-vaccination symptoms. In the end, the write-up presents real-time neural network-based applications to fight COVID-19 and a few machine learning and deep learning techniques to diagnose a COVID-19 infected person. The final part of the article concludes with an artificial neural network and statistical neural network-based approaches to identify the rate of infection risk in a country. © The Electrochemical Society
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021
Year:
2022
Document Type:
Article
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