ArticleJournal of medical Internet research2024
Potential Roles of Large Language Models in the Production of Systematic Reviews and Meta-Analyses.
Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
32 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Transforming evidence synthesis: A systematic review of the evolution of automated meta-analysis in the age of AI.Research synthesis methods · 2026Pooled it
- Improving reproducibility of Plasmodium falciparum culture: a large-language-model-driven literature review and a parasite growth variability assessment of donor red blood cells.Malaria journal · 2025Pooled it
- Can AI assess literature like experts? An entropy-based comparison of ChatGPT-4o, DeepSeek R1, and human ratings.Frontiers in research metrics and analytics · 2025Pooled it
- Moving towards acceleration with accountability: a conceptual framework for AI-assisted systematic reviews.Global epidemiology · 2026Article
- Design and methodology of the AI-empowered Clinical Evidence for Integrated Chinese-Western Medicine (ACE-iMed) platform.Integrative medicine research · 2026Article
- Integration of large language models and evidence-based Chinese medicine: A scoping review.Integrative medicine research · 2026Review
- Leveraging prompt-driven generative AI for systematic reviews in digital psychiatry: A stage-matched comparative proof-of-concept for healthcare researchers and clinicians.PLOS digital health · 2026Article
- Ensuring trustworthy AI assisted guideline development for clinical practice.NPJ digital medicine · 2026Article
- Value and Credibility of Meta-Analysis: Tutorial on Enhancing Methodological Rigor and AI-Powered Efficiency.Journal of medical Internet research · 2026Article
- How ChatGPT writes scientific titles in medical research: structural and content differences compared to human authors.Journal of the Medical Library Association : JMLA · 2026Article
- Evaluating Elicit's systematic reviews workflow in an umbrella review on air pollution and acute lower respiratory infections: a methodological study for quality appraisal.BMC medical research methodology · 2026Article
- Assessing the risk of bias of clinical trials with large language models and ROBUST-RCT: a feasibility study.Scientific reports · 2026Article
- Large language models in systematic review and meta-analysis of surgical treatments for vaginal vault prolapse.NPJ digital medicine · 2026Article
- Evaluating large language model performance in Risk of Bias assessments: A cross-sectional validation study.PloS one · 2026Article
- Automating the data extraction process for systematic reviews using GPT-4o and o3.Research synthesis methods · 2026Article
- Streamlining evidence based clinical recommendations with large language models.NPJ digital medicine · 2025Article
- Reporting guideline for the use of Generative Artificial intelligence tools in MEdical Research: the GAMER Statement.BMJ evidence-based medicine · 2025Article
- SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0.Analytical chemistry · 2025Article
- The AI-powered pathologist: A global survey mapping initial trends in AI adoption and outlook.Journal of pathology informatics · 2025Article
- A foundation model for human-AI collaboration in medical literature mining.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) such as ChatGPT have become widely applied in the field of medical research. In the process of conducting systematic reviews, similar tools can be used to expedite various steps, including defining clinical questions, performing the literature search, document screening, information extraction, and language refinement, thereby conserving resources and enhancing efficiency. However, when using LLMs, attention should be paid to transparent reporting, distinguishing between genuine and false content, and avoiding academic misconduct. In this viewpoint, we highlight the potential roles of LLMs in the creation of systematic reviews and meta-analyses, elucidating their advantages, limitations, and future research directions, aiming to provide insights and guidance for authors planning systematic reviews and meta-analyses.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.