Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools.
Journal:
Systematic reviews
PMID:
31727150
Abstract
BACKGROUND: We explored the performance of three machine learning tools designed to facilitate title and abstract screening in systematic reviews (SRs) when used to (a) eliminate irrelevant records (automated simulation) and (b) complement the work of a single reviewer (semi-automated simulation). We evaluated user experiences for each tool.