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Direct linkYuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
Moustgaard, Helene; Jones, Hayley E.; Savovic, Jelena; Clayton, Gemma L.; Sterne, Jonathan AC; Higgins, Julian PT; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2020
Randomized clinical trials underpin evidence-based clinical practice, but flaws in their conduct may lead to biased estimates of intervention effects and hence invalid treatment recommendations. The main approach to the empirical study of bias is to collate a number of meta-analyses and, within each, compare the results of trials with and without…
Descriptors: Epidemiology, Evidence, Medical Research, Intervention
Marshall, Iain J.; Noel-Storr, Anna; Kuiper, Joël; Thomas, James; Wallace, Byron C. – Research Synthesis Methods, 2018
Machine learning (ML) algorithms have proven highly accurate for identifying Randomized Controlled Trials (RCTs) but are not used much in practice, in part because the best way to make use of the technology in a typical workflow is unclear. In this work, we evaluate ML models for RCT classification (support vector machines, convolutional neural…
Descriptors: Randomized Controlled Trials, Accuracy, Computer Software, Classification
