Using automation to produce a ‘living map’ of the COVID-19 research literature

  • Ian Shemilt
  • Anneliese Arno
  • James Thomas EPPI Centre, UCL
  • Theo Lorenc
  • Claire C Khouja
  • Gary Raine
  • Katy Sutcliffe
  • Preethy D'Souza
  • Kath Wright
  • Amanda Sowden

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.
Published
2021-06-23
How to Cite
1.
Shemilt I, Arno A, Thomas J, Lorenc T, Khouja C, Raine G, Sutcliffe K, D’Souza P, Wright K, Sowden A. Using automation to produce a ‘living map’ of the COVID-19 research literature. JEAHIL [Internet]. 23Jun.2021 [cited 20Sep.2021];17(2):11-5. Available from: http://ojs.eahil.eu/ojs/index.php/JEAHIL/article/view/469
Section
Feature Articles