ArticleBMJ evidence-based medicine2025
Reporting guideline for the use of Generative Artificial intelligence tools in MEdical Research: the GAMER Statement.
Article in BMJ evidence-based medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The role of reviewers in the era of systematic reviews and meta-analysis: A practical guide for researchers.Biomolecules & biomedicine · 2025Guideline
- Scoping review of precision child and youth mental health research: dwelling in possibility.Frontiers in psychiatry · 2025Pooled it
- Integration of large language models and evidence-based Chinese medicine: A scoping review.Integrative medicine research · 2026Review
- Micro-TESE in Non-Obstructive Azoospermia: Phenotype-Guided Hormonal Optimization and Testosterone Response-Prognostic Biomarker or Therapeutic Target?Journal of clinical medicine · 2026Review
- Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.Rheumatology international · 2026Article
- A patient-derived benchmark for evaluating large language models in connective tissue diseases: blinded multi-stakeholder assessment and guideline comparison.Rheumatology international · 2026Observational
- Memorization in large language models in medicine prevalence characteristics and implications.Nature communications · 2026Article
- Evaluating the Methodological Quality of Artificial Intelligence-Assisted Systematic Reviews: Protocol for a Mixed Methods Meta-Research Study.JMIR research protocols · 2026Article
- A call for clarity: a unified checklist for reporting use of large language models in writing scientific manuscripts.Research integrity and peer review · 2026Article
- Postdilation Strategies Following Provisional Stenting of Left Main Coronary Bifurcations: Insights From Patient-Specific Computational Simulations.JACC. Advances · 2026Article
- Dental Anxiety as a Potential Bottleneck in Oral-Systemic Health Pathways: A Conceptual Mapping Review of Review Articles.Dentistry journal · 2026Review
- Article
- Assessing the risk of bias of clinical trials with large language models and ROBUST-RCT: a feasibility study.Scientific reports · 2026Article
- Evaluating AI-Generated Geriatric Case Studies for Interprofessional Education: Systematic Analysis Across 5 Platforms.JMIR medical education · 2026Article
- PhyCARE reporting guidelines for physiotherapy case reports: a consensus-based development .BMJ open · 2026Article
- Mapping and Quality Appraisal of Artificial Intelligence Preferential Reporting Checklists, Items, Guidelines, and Consensus in Healthcare: An Altmetric, Bibliometric, and Systematic Review.International journal of dentistry · 2026Article
- Transparent Reporting of AI in Systematic Literature Reviews: Development of the PRISMA-trAIce Checklist.JMIR AI · 2025Article
- Conducting Eating Disorder Research in the Era of Generative AI: Researcher Perspectives and Guidelines From the International Journal of Eating Disorders.The International journal of eating disorders · 2025Article
- Reporting guidelines for studies involving generative artificial intelligence applications: what do I use, and when?NPJ digital medicine · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesGenerative artificial intelligence (GAI) tools can enhance the quality and efficiency of medical research, but their improper use may result in plagiarism, academic fraud and unreliable findings. Transparent reporting of GAI use is essential, yet existing guidelines from journals and institutions are inconsistent, with no standardised principles. DESIGN AND
settingInternational online Delphi study.
participantsInternational experts in medicine and artificial intelligence.
main outcome measuresThe primary outcome measure is the consensus level of the Delphi expert panel on the items of inclusion criteria for GAMER (Rreporting guideline for the use of Generative Artificial intelligence tools in MEdical Research).
resultsThe development process included a scoping review, two Delphi rounds and virtual meetings. 51 experts from 26 countries participated in the process (44 in the Delphi survey). The final checklist comprises nine reporting items: general declaration, GAI tool specifications, prompting techniques, tool's role in the study, declaration of new GAI model(s) developed, artificial intelligence-assisted sections in the manuscript, content verification, data privacy and impact on conclusions.
conclusionGAMER provides universal and standardised guideline for GAI use in medical research, ensuring transparency, integrity and quality.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.