| Issue |
E3S Web of Conf.
Volume 469, 2023
The International Conference on Energy and Green Computing (ICEGC’2023)
|
|
|---|---|---|
| Article Number | 00070 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/e3sconf/202346900070 | |
| Published online | 20 December 2023 | |
Exploring Machine Learning contribution in COVID-19 cure and management: Predicting Mortality and Vaccine Efficacy: A survey
IESI Laboratory, ENSET Mohmmadia, Hassan 2nd University of Casablanca, Morocco
* Corresponding author: essamlali.ismail01@gmail.com
The SARS-CoV-2 virus, responsible for the COVID-19 pandemic, has left an indelible mark on a global scale. This illness, exhibiting a spectrum of mild to severe symptoms, has triggered a widespread health crisis. Within this context, Machine Learning has emerged as a versatile tool, playing a pivotal role in pandemic management. It has found applications in predicting virus transmission patterns, analyzing medical imaging data, and exploring potential therapeutic avenues. This comprehensive paper delves into the multifaceted involvement of Machine Learning in COVID-19 research, spanning from data aggregation to vaccine advancement. Furthermore, we delve into the ethical and societal dimensions inherent in leveraging Machine Learning for pandemic-related inquiries. In conclusion, we spotlight promising avenues for future exploration and advancement in this burgeoning field.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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