ArticleJournal of the American Medical Informatics Association : JAMIA2025
Automated analyses of risk of bias and critical appraisal of systematic reviews (ROBIS and AMSTAR 2): a comparison of the performance of 4 large language models.
Article in Journal of the American Medical Informatics Association : JAMIA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effects on mortality of different blood purification techniques in sepsis patients: an umbrella review of systematic reviews and meta-analyses.Renal failure · 2026Pooled it
- Lower-limb biomechanical alterations across movement tasks in individuals with chronic ankle instability: An umbrella review of systematic reviews and meta-analyses.Mechanobiology in medicine · 2026Review
- Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis.JMIR medical informatics · 2026Article
- Potential and Limitations of Large Language Models for Medical Literature Analysis: A Preliminary Investigation.Cureus · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
objectivesTo explore the performance of 4 large language model (LLM) chatbots for the analysis of 2 of the most commonly used tools for the advanced analysis of systematic reviews (SRs) and meta-analyses. MATERIALS AND
methodsWe explored the performance of 4 LLM chatbots (ChatGPT, Gemini, DeepSeek, and QWEN) for the analysis of ROBIS and AMSTAR 2 tools (sample sizes: 20 SRs), in comparison with assessments by human experts.
resultsGemini showed the best agreement with human experts for both ROBIS and AMSTAR 2 (accuracy: 58% and 70%). The second best LLM chatbots were ChatGPT and QWEN, for ROBIS and AMSTAR 2, respectively. DISCUSSION: Some LLM chatbots underestimated the risk of bias or overestimated the confidence of the results in published SRs, which is compatible with recent articles for other tools.
conclusionThis is one of the first studies comparing the performance of several LLM chatbots for the automated analyses of ROBIS and AMSTAR 2.
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Registered trials
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