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. 2024 Jan 12;229(1):7-9.
doi: 10.1093/infdis/jiad224.

Lessons (Machine) Learned From COVID-19

Timothy Sullivan  1
Affiliations

Lessons (Machine) Learned From COVID-19

Timothy Sullivan. J Infect Dis. .

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.

Keywords: COVID-19; SARS-CoV-2; biomedical publishing; machine learning.

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Conflict of interest statement

Potential conflicts of interest. The author: No reported conflicts of interest. The author has submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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