Machine learning applications to COVID-19: a state-of-the-art survey

Date

2022

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers Inc.

Abstract

There exists a large and rapidly growing body of literature related to applications of machine learning to Covid-19. Given the substantial volume of research, there is a need to organize and categorize the literature. In this paper, we provide the most up-to-date review as of the beginning of 2022. We propose an application-based taxonomy to group the existing literature and provide an analysis of the research in each category. We discuss the progress as well as the pitfalls of the existing research, and propose keys for improvement. © 2022 IEEE.

Description

Keywords

CNN, Covid-19, deep learning, LSTM, machine learning, review

Citation

Kamalov, F., Cherukuri, A. K., & Thabtah, F. (2022). Machine learning applications to COVID-19: A state-of-the-art survey. 2022 Advances in Science and Engineering Technology International Conferences (ASET). https://doi.org/10.1109/ASET53988.2022.9734959

DOI