Automating risk of bias assessment in systematic reviews: a real-time mixed methods comparison of human researchers to a machine learning system

Automating risk of bias assessment in systematic reviews: a real-time mixed methods comparison of human researchers to a machine learning system

Abstract Background Machine learning and automation are increasingly used to make the evidence synthesis process faster and more responsive to policymakers’ needs. In systematic reviews of randomized controlled trials (RCTs), risk of bias assessment is a resource-intensive task that typically requir...

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Bibliographic Details
Main Authors: Patricia Sofia Jacobsen Jardim, Christopher James Rose, Heather Melanie Ames, Jose Francisco Meneses Echavez, Stijn Van de Velde, Ashley Elizabeth Muller
Format: Article
Language:English
Published: BMC 2022-06-01
Series:BMC Medical Research Methodology
Subjects:
Risk of bias
Machine learning
Automation
Evidence synthesis
Systematic review
Heath technology assessment
Online Access:https://doi.org/10.1186/s12874-022-01649-y

Internet

https://doi.org/10.1186/s12874-022-01649-y

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