Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools

ConclusionsThe workload savings afforded in the automated simulation came with increased risk of missing relevant records. Supplementing a single reviewer ’s decisions with relevance predictions (semi-automated simulation) sometimes reduced the proportion missed, but performance varied by tool and SR. Designing tools based on reviewers’ self-identified preferences may improve their compatibility with present workflows.Systematic review registrationNot applicable.
Source: Systematic Reviews - Category: International Medicine & Public Health Source Type: research