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Direct linkXu, Chang; Ju, Ke; Lin, Lifeng; Jia, Pengli; Kwong, Joey S. W.; Syed, Asma; Furuya-Kanamori, Luis – Research Synthesis Methods, 2022
Rapid reviews have been widely employed to support timely decision-making, and limiting the search date is the most popular approach in published rapid reviews. We assessed the accuracy and workload of search date limits on the meta-analytical results to determine the best rapid strategy. The meta-analyses data were collected from the Cochrane…
Descriptors: Evidence, Synthesis, Accuracy, Meta Analysis
Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Ian Thomas; Shannon Kugley; Karen Crotty; Meera Viswanathan; Barbara Nussbaumer-Streit; Graham Booth; Nathaniel Erskine; Amanda Konet; Robert Chew – Research Synthesis Methods, 2024
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…
Descriptors: Data Collection, Evidence, Synthesis, Language Processing
Perlman-Arrow, Sara; Loo, Noel; Bobrovitz, Niklas; Yan, Tingting; Arora, Rahul K. – Research Synthesis Methods, 2023
The laborious and time-consuming nature of systematic review production hinders the dissemination of up-to-date evidence synthesis. Well-performing natural language processing (NLP) tools for systematic reviews have been developed, showing promise to improve efficiency. However, the feasibility and value of these technologies have not been…
Descriptors: Natural Language Processing, Screening Tests, COVID-19, Pandemics
Metzendorf, Maria-Inti; Featherstone, Robin M. – Research Synthesis Methods, 2021
The Cochrane COVID-19 Study Register (CCSR) is a public, continually updated database of COVID-19 study references. The aim of this study-based register is to support rapid and living evidence synthesis, including an evidence ecosystem of COVID-19 research (CEOsys). In November and December 2020, we conducted an evaluation of the CCSR for CEOsys,…
Descriptors: COVID-19, Pandemics, Databases, Accuracy
