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Direct linkMizutani, Shosuke; Zhou, Yi; Tian, Yu-Shi; Takagi, Tatsuya; Ohkubo, Tadayasu; Hattori, Satoshi – Research Synthesis Methods, 2023
Meta-analysis of diagnostic test accuracy (DTA) is a powerful statistical method for synthesizing and evaluating the diagnostic capacity of medical tests and has been extensively used by clinical physicians and healthcare decision-makers. However, publication bias (PB) threatens the validity of meta-analysis of DTA. Some statistical methods have…
Descriptors: Meta Analysis, Diagnostic Tests, Accuracy, Publications
Qusai Khraisha; Sophie Put; Johanna Kappenberg; Azza Warraitch; Kristin Hadfield – Research Synthesis Methods, 2024
Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…
Descriptors: Peer Evaluation, Research Reports, Artificial Intelligence, Computer Software
Turner, Simon Lee; Korevaar, Elizabeth; Cumpston, Miranda S.; Kanukula, Raju; Forbes, Andrew B.; McKenzie, Joanne E. – Research Synthesis Methods, 2023
Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis. While publications of ITS rarely provide…
Descriptors: Quasiexperimental Design, Graphs, Accuracy, Computation
Wang, Junfeng; Keusters, Willem R.; Wen, Lingzi; Leeflang, Mariska M. G. – Research Synthesis Methods, 2021
Background: Individual patient data meta-analyses (IPD-MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD-MA have been published in recent years, but there is much variation in how these IPD-MA were…
Descriptors: Diagnostic Tests, Accuracy, Patients, Meta Analysis
Armijo-Olivo, Susan; Craig, Rodger; Campbell, Sandy – Research Synthesis Methods, 2020
Background: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can decrease the time and burden by automating the process, but evidence validating such software is…
Descriptors: Comparative Analysis, Computer Software, Decision Making, Randomized Controlled Trials
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
