Shemilt, I;
Arno, A;
Thomas, J;
Lorenc, T;
Khouja, CC;
Raine, G;
Sutcliffe, K;
... Sowden, A; + view all
(2021)
Using automation to produce a ‘living map’ of the COVID-19 research literature.
Journal of EAHIL
, 17
(2)
pp. 11-15.
10.32384/jeahil17469.
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Abstract
The COVID-19 pandemic has disrupted life worldwide and presented unique challenges in the health evidencesynthesis space. The urgent nature of the pandemic required extreme rapidity for keeping track of research, andthis presented a unique opportunity for long-proposed automation systems to be deployed and evaluated. Wecompared the use of novel automation technologies with conventional manual screening; and Microsoft AcademicGraph (MAG) with the MEDLINE and Embase databases locating the emerging research evidence. We foundthat a new workflow involving machine learning to identify relevant research in MAG achieved a much higherrecall with lower manual effort than using conventional approaches.
| Type: | Article |
|---|---|
| Title: | Using automation to produce a ‘living map’ of the COVID-19 research literature |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.32384/jeahil17469 |
| Publisher version: | https://doi.org/10.32384/jeahil17469 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. JEAHIL is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence, unless otherwise stated. Please read our Policies page for more information on Open Access, copyright and permissions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137559 |
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