Abstract
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.
Cite
CITATION STYLE
Essamlali, I., El Khaili, M., & Nhaila, H. (2023). Exploring Machine Learning contribution in COVID-19 cure and management: Predicting Mortality and Vaccine Efficacy: A survey. In E3S Web of Conferences (Vol. 469). EDP Sciences. https://doi.org/10.1051/e3sconf/202346900070
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.