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Amanda Konet; Ian Thomas; Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Shannon Kugley; Karen Crotty; Meera Viswanathan; Robert Chew – Research Synthesis Methods, 2024
Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT-4) for…
Descriptors: Data Collection, Artificial Intelligence, Computer Software, Computer System Design
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
Owen, Rhiannon K.; Bradbury, Naomi; Xin, Yiqiao; Cooper, Nicola; Sutton, Alex – Research Synthesis Methods, 2019
Background: Network meta-analysis (NMA) is a powerful analysis method used to identify the best treatments for a condition and is used extensively by health care decision makers. Although software routines exist for conducting NMA, they require considerable statistical programming expertise to use, which limits the number of researchers able to…
Descriptors: Network Analysis, Meta Analysis, Computer Software, Medical Research