The semi-automation of title and abstract screening: a retrospective exploration of ways to leverage Abstrackr's relevance predictions in systematic and rapid reviews.

Journal: BMC medical research methodology
Published Date:

Abstract

BACKGROUND: We investigated the feasibility of using a machine learning tool's relevance predictions to expedite title and abstract screening.

Authors

  • Allison Gates
    Alberta Research Centre for Health Evidence (ARCHE), Department of Pediatrics, University of Alberta, 4-472, Edmonton Clinic Health Academy, 11405-87 Avenue NW, Edmonton, Alberta T6G 1C9, Canada.
  • Michelle Gates
    Alberta Research Centre for Health Evidence, Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada.
  • Meghan Sebastianski
    Alberta Strategy for Patient-Oriented Research (SPOR) SUPPORT Unit Knowledge Translation Platform, University of Alberta, Edmonton, Alberta, Canada.
  • Samantha Guitard
    Department of Pediatrics, Alberta Research Centre for Health Evidence and the University of Alberta Evidence-based Practice Center, University of Alberta, 11405 87 Ave NW, Edmonton, Alberta, T6G 1C9, Canada.
  • Sarah A Elliott
    Department of Pediatrics, Alberta Research Centre for Health Evidence and the University of Alberta Evidence-based Practice Center, University of Alberta, 11405 87 Ave NW, Edmonton, Alberta, T6G 1C9, Canada.
  • Lisa Hartling
    Alberta Research Centre for Health Evidence (ARCHE), Department of Pediatrics, University of Alberta, 4-472, Edmonton Clinic Health Academy, 11405-87 Avenue NW, Edmonton, Alberta T6G 1C9, Canada. Electronic address: hartling@ualberta.ca.