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Large language models for the screening step in systematic reviews in dentistry
10 references·1 citing·43 second hopsampled
Large language models for the screening step in systematic reviews in dentistry (2025)Large language models for the screening s…Title and abstract screening for literature reviews using large language models: an exploratory study in the biomedical domain (2024)Title and abstract screening …Screening articles for systematic reviews with ChatGPT (2024)Screening articles for system…Evaluating the effectiveness of large language models in abstract screening: a comparative analysis (2024)Evaluating the effectiveness …Automated Paper Screening for Clinical Reviews Using Large Language Models: Data Analysis Study (2023)Automated Paper Screening for…Using artificial intelligence methods for systematic review in health sciences: A systematic review (2022)Using artificial intelligence…Automation of systematic literature reviews: A systematic literature review (2021)Automation of systematic lite…Decoding semi-automated title-abstract screening: findings from a convenience sample of reviews (2020)Decoding semi-automated title…An evaluation of DistillerSR’s machine learning-based prioritization tool for title/abstract screening – impact on reviewer-relevant outcomes (2020)An evaluation of DistillerSR’…Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool (2018)Technology-assisted title and…Prioritising references for systematic reviews with RobotAnalyst: A user study (2018)Prioritising references for s…Accuracy of LLMs to retrieve numeric data for meta-analysis in dentistry (2025)Accuracy of LLMs to retrieve …Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)Tools to support the automation of systematic reviews: a scoping review (2021)Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up? (2010)On the Complexity of Best Arm Identification in Multi-Armed Bandit Models (2014)Rayyan—a web and mobile app for systematic reviews (2016)An automated approach to identifying search terms for systematic reviews using keyword co‐occurrence networks (2019)Toward systematic review automation: a practical guide to using machine learning tools in research synthesis (2019)A typology of reviews: an analysis of 14 review types and associated methodologies (2009)Evidence summaries: the evolution of a rapid review approach (2012)What kind of systematic review should I conduct? A proposed typology and guidance for systematic reviewers in the medical and health sciences (2018)The SAFE procedure: a practical stopping heuristic for active learning-based screening in systematic reviews and meta-analyses (2024)Scoping studies: towards a methodological framework (2005)Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement (2015)Reducing Literature Screening Workload With Machine Learning (2023)Updated recommendations for the Cochrane rapid review methods guidance for rapid reviews of effectiveness (2024)How Quickly Do Systematic Reviews Go Out of Date? A Survival Analysis (2007)Using text mining for study identification in systematic reviews: a systematic review of current approaches (2015)A full systematic review was completed in 2 weeks using automation tools: a case study (2020)Artificial intelligence and the conduct of literature reviews (2021)Artificial intelligence to automate the systematic review of scientific literature (2023)Artificial intelligence and illusions of understanding in scientific research (2024)AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both (2017)School Closures During Social Lockdown and Mental Health, Health Behaviors, and Well-being Among Children and Adolescents During the First COVID-19 Wave (2022)Artificial intelligence in systematic reviews: promising when appropriately used (2023)Data extraction for evidence synthesis using a large language model: A proof‐of‐concept study (2024)Cochrane Handbook for Systematic Reviews of Interventions (2020)An open source machine learning framework for efficient and transparent systematic reviews (2021)Generative artificial intelligence use in evidence synthesis: A systematic review (2025)The emergence of large language models as tools in literature reviews: a large language model-assisted systematic review (2025)How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses (2018)ASReview LAB v.2: Open-source text screening with multiple agents and a crowd of experts (2025)Large Language Models in Systematic Review Screening: Opportunities, Challenges, and Methodological Considerations (2025)Streamlining systematic reviews with large language models using prompt engineering and retrieval augmented generation (2025)GPT-3: Its Nature, Scope, Limits, and Consequences (2020)PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews (2020)Accelerating clinical evidence synthesis with large language models (2025)Enhancing systematic literature reviews with generative artificial intelligence: development, applications, and performance evaluation (2025)Large Language Model for Qualitative Research: A Systematic Mapping Study (2025)Cochrane Handbook for Systematic Reviews of Interventions (2008)Leveraging artificial intelligence to enhance systematic reviews in health research: advanced tools and challenges (2024)Large language models for automated scholarly paper review: A survey (2025)
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References

  • 2021Automation of systematic literature reviews: A systematic literature review494 cited
  • 2023Automated Paper Screening for Clinical Reviews Using Large Language Models: Data Analysis Study259 cited
  • 2022Using artificial intelligence methods for systematic review in health sciences: A systematic review250 cited
  • 2024Title and abstract screening for literature reviews using large language models: an exploratory study in the biomedical domain188 cited
  • 2018Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool152 cited
  • 2024Evaluating the effectiveness of large language models in abstract screening: a comparative analysis152 cited
  • 2018Prioritising references for systematic reviews with RobotAnalyst: A user study148 cited
  • 2020An evaluation of DistillerSR’s machine learning-based prioritization tool for title/abstract screening – impact on reviewer-relevant outcomes140 cited
  • 2024Screening articles for systematic reviews with ChatGPT99 cited
  • 2020Decoding semi-automated title-abstract screening: findings from a convenience sample of reviews31 cited

Cited by

  • 2025Accuracy of LLMs to retrieve numeric data for meta-analysis in dentistry7 cited

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