Abstract
Since coronavirus disease 2019 (COVID-19) first emerged more than 3 years ago, more than 1200 articles have been written describing "lessons learned"from the pandemic. While these articles may contain valuable insights, reading them all would be impossible. A machine learning clustering analysis was therefore performed to obtain an overview of these publications and to highlight the benefits of using machine learning to analyze the vast and ever-growing COVID-19 literature.
Original language | English |
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Pages (from-to) | 7-9 |
Number of pages | 3 |
Journal | Journal of Infectious Diseases |
Volume | 229 |
Issue number | 1 |
DOIs | |
State | Published - 15 Jan 2024 |
Keywords
- COVID-19
- SARS-CoV-2
- biomedical publishing
- machine learning