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Performance of active learning models for screening prioritization in systematic reviews: a simulation study into the Average Time to Discover relevant records
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Performance of active learning models for screening prioritization in systematic reviews: a simulation study into the Average Time to Discover relevant records (2023)Performance of active learning models for…An open source machine learning framework for efficient and transparent systematic reviews (2021)An open source machine learni…Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation (2020)Software tools to support tit…Using machine learning to advance synthesis and use of conservation and environmental evidence (2018)Using machine learning to adv…Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool (2018)Technology-assisted title and…Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry (2017)Analysis of the time and work…The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies (2016)The GRoLTS-Checklist: Guideli…Rayyan—a web and mobile app for systematic reviews (2016)Rayyan—a web and mobile app f…Using text mining for study identification in systematic reviews: a systematic review of current approaches (2015)Using text mining for study i…Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement (2015)Preferred reporting items for…Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers (2015)Faster title and abstract scr…Erratum to: Using text mining for study identification in systematic reviews: a systematic review of current approaches (2015)Erratum to: Using text mining…Reducing systematic review workload through certainty-based screening (2014)Reducing systematic review wo…Pinpointing needles in giant haystacks: use of text mining to reduce impractical screening workload in extremely large scoping reviews (2013)Pinpointing needles in giant …Deploying an interactive machine learning system in an evidence-based practice center (2012)Deploying an interactive mach…Semi-automated screening of biomedical citations for systematic reviews (2010)Semi-automated screening of b…Reducing Workload in Systematic Review Preparation Using Automated Citation Classification (2005)Reducing Workload in Systemat…The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence (2026)The AI risk repository: A met…Utilizing Large language models to select literature for meta-analysis shows workload reduction while maintaining a similar recall level as manual curation (2025)Utilizing Large language mode…Testing the utility of GPT for title and abstract screening in environmental systematic evidence synthesis (2025)Testing the utility of GPT fo…ASReview LAB v.2: Open-source text screening with multiple agents and a crowd of experts (2025)ASReview LAB v.2: Open-source…Utilizing ASReview in screening primary studies for meta-research in SLA: A step-by-step tutorial (2024)Utilizing ASReview in screeni…Systematic review using a spiral approach with machine learning (2024)Systematic review using a spi…Reproducibility and Data Storage for Active Learning-Aided Systematic Reviews (2024)Reproducibility and Data Stor…Papers that summarise other papers (systematic reviews and meta‐analyses) (2024)Papers that summarise other p…Machine learning to optimize literature screening in medical guideline development (2024)Machine learning to optimize …Health behavior interventions among people with lower socio-economic position: a scoping review of behavior change techniques and effectiveness (2024)Health behavior interventions…Harnessing artificial intelligence for efficient systematic reviews: A case study in ecosystem condition indicators (2024)Harnessing artificial intelli…Fostering Artificial Intelligence-based supports for informal caregivers: a systematic review of the literature (2024)Fostering Artificial Intellig…Assessing the article screening efficiency of artificial intelligence for Systematic Reviews (2024)Assessing the article screeni…Addressing the challenges of reconstructing systematic reviews datasets: a case study and a noisy label filter procedure (2024)Addressing the challenges of …Can artificial intelligence separate the wheat from the chaff in systematic reviews of health economic articles? (2023)Can artificial intelligence s…Active learning-based systematic reviewing using switching classification models: the case of the onset, maintenance, and relapse of depressive disorders (2023)Active learning-based systema…The American Heritage Word Frequency Book (1973)Developing Optimal Search Strategies for Detecting Clinically Sound Studies in MEDLINE (1994)Automating data extraction in systematic reviews: a systematic review (2015)Systematic Reviews: Rationale for systematic reviews (1994)Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up? (2010)An Introduction to Systematic Reviews (2013)Evidence & Gap Maps: A tool for promoting evidence informed policy and strategic research agendas (2016)Living systematic reviews: 2. Combining human and machine effort (2017)The value of a second reviewer for study selection in systematic reviews (2019)The Measurement of Observer Agreement for Categorical Data (1977)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)The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)Health Measurement Scales: A Practical Guide to Their Development and Use (1989)Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study (2007)Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using M plus (2014)Characterizing Developmental Trajectories and the Role of Neuropsychiatric Genetic Risk Variants in Early-Onset Depression (2018)Re-evaluating the notion that resilience is commonplace: A review and distillation of directions for future research, practice, and policy (2018)The Application of Latent Class Analysis for Investigating Population Child Mental Health: A Systematic Review (2019)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Digital Mental Health Interventions for Depression, Anxiety, and Enhancement of Psychological Well-Being Among College Students: Systematic Review (2019)Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review (2021)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Research Screener: a machine learning tool to semi-automate abstract screening for systematic reviews (2021)Tools to support the automation of systematic reviews: a scoping review (2021)Artificial intelligence for literature reviews: opportunities and challenges (2024)The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration (2009)Promoting an open research culture (2015)Artificial intelligence and the conduct of literature reviews (2021)Artificial intelligence in systematic reviews: promising when appropriately used (2023)Systematic review automation technologies (2014)Online tools supporting the conduct and reporting of systematic reviews and systematic maps: a case study on CADIMA and review of existing tools (2018)Best practice guidelines for abstract screening large‐evidence systematic reviews and meta‐analyses (2019)Interrater Reliability in Systematic Review Methodology: Exploring Variation in Coder Decision-Making (2018)Toward systematic review automation: a practical guide to using machine learning tools in research synthesis (2019)A full systematic review was completed in 2 weeks using automation tools: a case study (2020)Searching for and selecting studies (2019)Single screening versus conventional double screening for study selection in systematic reviews: a methodological systematic review (2019)
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References

  • 2015Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement26,189 cited
  • 2016Rayyan—a web and mobile app for systematic reviews25,980 cited
  • 2021An open source machine learning framework for efficient and transparent systematic reviews1,149 cited
  • 2017Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry733 cited
  • 2016The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies721 cited
  • 2015Using text mining for study identification in systematic reviews: a systematic review of current approaches680 cited
  • 2012Deploying an interactive machine learning system in an evidence-based practice center530 cited
  • 2020Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation448 cited
  • 2005Reducing Workload in Systematic Review Preparation Using Automated Citation Classification410 cited
  • 2015Erratum to: Using text mining for study identification in systematic reviews: a systematic review of current approaches353 cited
  • 2010Semi-automated screening of biomedical citations for systematic reviews351 cited
  • 2014Reducing systematic review workload through certainty-based screening190 cited
  • 2015Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers

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184 cited
  • 2013Pinpointing needles in giant haystacks: use of text mining to reduce impractical screening workload in extremely large scoping reviews170 cited
  • 2018Using machine learning to advance synthesis and use of conservation and environmental evidence155 cited
  • 2018Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool148 cited
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    • 2024Utilizing ASReview in screening primary studies for meta-research in SLA: A step-by-step tutorial63 cited
    • 2023Can artificial intelligence separate the wheat from the chaff in systematic reviews of health economic articles?50 cited
    • 2026The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence48 cited
    • 2023Active learning-based systematic reviewing using switching classification models: the case of the onset, maintenance, and relapse of depressive disorders36 cited
    • 2024Machine learning to optimize literature screening in medical guideline development21 cited
    • 2024Assessing the article screening efficiency of artificial intelligence for Systematic Reviews21 cited
    • 2025Utilizing Large language models to select literature for meta-analysis shows workload reduction while maintaining a similar recall level as manual curation20 cited
    • 2025ASReview LAB v.2: Open-source text screening with multiple agents and a crowd of experts20 cited
    • 2024Papers that summarise other papers (systematic reviews and meta‐analyses)20 cited
    • 2024Reproducibility and Data Storage for Active Learning-Aided Systematic Reviews18 cited
    • 2025Testing the utility of GPT for title and abstract screening in environmental systematic evidence synthesis17 cited
    • 2024Addressing the challenges of reconstructing systematic reviews datasets: a case study and a noisy label filter procedure14 cited
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    • 2024Health behavior interventions among people with lower socio-economic position: a scoping review of behavior change techniques and effectiveness11 cited