Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach

摘要

ObjectivesIdentifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML.