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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 11, NOVEMBER 2021

Analysis on Psychosocial Disorder in Children During Post-COVID Education – A Machine Learning Approach

Dillip Narayan Sahu, Pankajini Sahu

DOI: 10.17148/IJARCCE.2021.101102

Abstract: As SARS COVID is continues to spread in the world also in India as well, the growth rate of detection of COVID cases might be non-exponential but the actual cases and data and its effect towards the new generation especially in the case of children, the impact is a very serious issue. The current situation not only affects the economic and health condition of the country but also in the psychological context to the whole society across the nation. In the situation of a complete lockdown, a kind of restriction to the children for there open movements may be restricted from playing, schooling, any kind of physical contact with outsiders, socialization are all directly or indirectly leading to a more isolated behavioral impact towards the brain or mindset of the children. In this paper, we have shown some real-time experiments and observations with the help of some predictive analysis and algorithms which clearly shows the impact of COVID in children as a real case of Psychosocial Disorder.

Keywords: Algorithm, COVID, Education, Machine Learning, Psychosocial Disorder.

How to Cite:

[1] Dillip Narayan Sahu, Pankajini Sahu, “Analysis on Psychosocial Disorder in Children During Post-COVID Education – A Machine Learning Approach,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.101102