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8th International Conference on Fuzzy Systems and Data Mining, FSDM 2022
; 358:181-190, 2022.
Article
in English
| Scopus | ID: covidwho-2141608
ABSTRACT
Recently, many research works adopt machine learning to provide accurate predictions on the COVID-19 pandemic. In this paper, we design and develop a web system which adopts machine learning methodologies to provide data analysis and data visualization. For experiment analytics results in the system, we find that SVM method outperforms LR method in every use case. We propose a web-based user-friendly and intuitive COVID-19 information hub, which can improve data accessibility to the public and allow more accurate decision-making to help fight the pandemic. © 2022 The authors and IOS Press.