Analyzing the vast coronavirus literature with CoronaCentral, 2021, Lever and Altman

Abstract

The SARS-CoV-2 pandemic has caused a surge in research exploring all aspects of the virus and its effects on human health. The overwhelming publication rate means that researchers are unable to keep abreast of the literature. To ameliorate this, we present the CoronaCentral resource that uses machine learning to process the research literature on SARS-CoV-2 together with SARS-CoV and MERS-CoV. We categorize the literature into useful topics and article types and enable analysis of the contents, pace, and emphasis of research during the crisis with integration of Altmetric data. These topics include therapeutics, disease forecasting, as well as growing areas such as “long COVID” and studies of inequality. This resource, available at https://coronacentral.ai, is updated daily.

Open access, https://www.pnas.org/content/118/23/e2100766118

 

but will the machine code be able to cut out the useless copy paste dross that seems to be produced in ever greater numbers because of the broken systems involved plus wilful deceit by the usual crowd.