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
item.page.type
Conference Paper
item.page.format
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