Proceedings of the International Seminar of Science and Applied Technology (ISSAT 2020)

Battle of COVID-19: Where We Can Take The Help Of Machine Learning To Win?

Authors
Wathiq Mansoor, Yashbir Singh
Corresponding Author
Wathiq Mansoor
Available Online 22 December 2020.
DOI
10.2991/aer.k.201221.002How to use a DOI?
Keywords
Pandemic era, COVID19, Artificial intelligence, Deep learning, Radiology, Robotics
Abstract

COVID-19 is caused by Coronavirus which has been previously linked with 2012 SARS disease. This is an RNA virus. Highly contagious is nature; spreads by air droplet and contact. It needs both air and contact precautions. Interventions to prevent its spread have been tried which includes social distancing, preventing skin contact with the patient and handwashing with soap. Use of sanitizers with >60% alcohol content has been useful. In scientific methods including pre-detection of signs and symptoms help to prevent the spread by quarantining the sick from the healthy for a period of at least 2 weeks. We can use the technology known to us; here, in this short communication, we have focused to show the basic picture of updated technology which is Artificial Intelligence.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Seminar of Science and Applied Technology (ISSAT 2020)
Series
Advances in Engineering Research
Publication Date
22 December 2020
ISBN
10.2991/aer.k.201221.002
ISSN
2352-5401
DOI
10.2991/aer.k.201221.002How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Wathiq Mansoor
AU  - Yashbir Singh
PY  - 2020
DA  - 2020/12/22
TI  - Battle of COVID-19: Where We Can Take The Help Of Machine Learning To Win?
BT  - Proceedings of the International Seminar of Science and Applied Technology (ISSAT 2020)
PB  - Atlantis Press
SP  - 8
EP  - 10
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201221.002
DO  - 10.2991/aer.k.201221.002
ID  - Mansoor2020
ER  -