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Sutton, Anthea; O'Keefe, Hannah; Johnson, Eugenie Evelynne; Marshall, Christopher – Research Synthesis Methods, 2023
The Systematic Review Toolbox aims provide a web-based catalogue of tools that support various tasks within the systematic review and wider evidence synthesis process. Identifying publications surrounding specific systematic review tools is currently challenging, leading to a high screening burden for few eligible records. We aimed to develop a…
Descriptors: Search Strategies, Automation, Evidence, Synthesis
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Wanner, Amanda; Baumann, Niki – Research Synthesis Methods, 2019
Background: Both PubMed and Ovid MEDLINE contain records from the MEDLINE database. However, there are subtle differences in content, functionality, and search syntax between the two. There are many instances in which researchers may wish to search both interfaces, such as when conducting supplementary searching for a systematic review to retrieve…
Descriptors: Search Strategies, Databases, Medical Research, Medical Evaluation
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Günhan, Burak Kürsad; Röver, Christian; Friede, Tim – Research Synthesis Methods, 2020
Meta-analyses of clinical trials targeting rare events face particular challenges when the data lack adequate numbers of events for all treatment arms. Especially when the number of studies is low, standard random-effects meta-analysis methods can lead to serious distortions because of such data sparsity. To overcome this, we suggest the use of…
Descriptors: Meta Analysis, Medical Research, Drug Therapy, Bayesian Statistics
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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