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 requires two trained reviewers. One function of RobotReviewer, an off-the-shelf machine learning system, is an automated risk of bias assessment.

Methods

We assessed the feasibility of adopting RobotReviewer within a national public health institute using a randomized, real-time, user-centered study. The study included 26 RCTs and six reviewers from two projects examining health and social interventions. We randomized these studies to one of two RobotReviewer platforms. We operationalized feasib

SUBMITTER: Jardim PSJ 

PROVIDER: S-EPMC9174024 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature