The effect of machine learning tools for evidence synthesis on resource use and time-to-completion: protocol for a retrospective pilot study.

Journal: Systematic reviews
Published Date:

Abstract

BACKGROUND: Machine learning (ML) tools exist that can reduce or replace human activities in repetitive or complex tasks. Yet, ML is underutilized within evidence synthesis, despite the steadily growing rate of primary study publication and the need to periodically update reviews to reflect new evidence. Underutilization may be partially explained by a paucity of evidence on how ML tools can reduce resource use and time-to-completion of reviews.

Authors

  • Ashley Elizabeth Muller
    Norwegian Institute of Public Health, Skøyen, Norway.
  • Rigmor C Berg
    Norwegian Institute of Public Health, Oslo, Norway.
  • Jose Francisco Meneses-Echavez
    Norwegian Institute of Public Health, Oslo, Norway.
  • Heather M R Ames
    Norwegian Institute of Public Health, Oslo, Norway.
  • Tiril C Borge
    Norwegian Institute of Public Health, Oslo, Norway.
  • Patricia Sofia Jacobsen Jardim
    Norwegian Institute of Public Health, Skøyen, Norway.
  • Chris Cooper
    Bristol Medical School, University of Bristol, Bristol, UK.
  • Christopher James Rose
    Norwegian Institute of Public Health, Skøyen, Norway.