Accuracy and Efficiency of Machine Learning-Assisted Risk-of-Bias Assessments in "Real-World" Systematic Reviews : A Noninferiority Randomized Controlled Trial.

Journal: Annals of internal medicine
Published Date: May 31, 2022

Abstract

BACKGROUND: Automation is a proposed solution for the increasing difficulty of maintaining up-to-date, high-quality health evidence. Evidence assessing the effectiveness of semiautomated data synthesis, such as risk-of-bias (RoB) assessments, is lacking.

Authors

  • Anneliese Arno
    EPPI-Centre, UCL Social Research Institute, University College London, London, London, WC1H 0NR, UK.
  • James Thomas
    EPPI-Centre, Social Research Institute, University College London, London, England, UK.
  • Byron Wallace
    College of Computer and Information Science, Northeastern University, 360 Huntington Ave, Boston, MA 02115, USA.
  • Iain J Marshall
    Department of Primary Care and Public Health Sciences, King's College London, UK iain.marshall@kcl.ac.uk.
  • Joanne E McKenzie
    School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia (J.E.M., J.H.E.).
  • Julian H Elliott
    School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia (J.E.M., J.H.E.).

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