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Building a Systematic Online Living Evidence Summary of COVID-19 Research

Hair, K; Sena, ES; Wilson, E; Currie, G; Macleod, M; Bahor, Z; Sena, C; ... Drury, B; + view all (2021) Building a Systematic Online Living Evidence Summary of COVID-19 Research. Journal of EAHIL , 17 (2) pp. 21-26. 10.32384/jeahil17465. Green open access

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Abstract

Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence.

Type: Article
Title: Building a Systematic Online Living Evidence Summary of COVID-19 Research
Open access status: An open access version is available from UCL Discovery
DOI: 10.32384/jeahil17465
Publisher version: https://doi.org/10.32384/jeahil17465
Language: English
Additional information: © 2021 Journal of the European Association for Health Information and Libraries. This work is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Keywords: COVID-19; evidence synthesis; machine learning; web application; database
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
URI: https://discovery.ucl.ac.uk/id/eprint/10136539
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