Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews.

Journal: Journal of clinical epidemiology
Published Date: May 1, 2021

Abstract

OBJECTIVES: This study developed, calibrated, and evaluated a machine learning classifier designed to reduce study identification workload in Cochrane for producing systematic reviews.

Authors

  • James Thomas
    EPPI-Centre, Social Research Institute, University College London, London, England, UK.
  • Steve McDonald
    Cochrane Australia, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
  • Anna Noel-Storr
    Cochrane Dementia and Cognitive Improvement Group University of Oxford United Kingdom.
  • Ian Shemilt
    EPPI-Centre, UCL Social Research Institute, University College London, London, London, WC1H 0NR, UK.
  • Julian Elliott
    Cochrane Australia, School of Public Health and Preventive Medicine, Monash University, 99 Commercial Road, Melbourne VIC 3004, Australia; Department of Infectious Diseases, Monash University and Alfred Hospital, 55 Commercial Rd, Melbourne VIC 3004, Australia.
  • Chris Mavergames
    Cochrane, St Albans House, 57-59 Haymarket, London SW1Y 4QX, UK.
  • Iain J Marshall
    Department of Primary Care and Public Health Sciences, King's College London, UK iain.marshall@kcl.ac.uk.

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