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Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool

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References

2009Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement83,813 cited
2009Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement63,979 cited
2009Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.44,857 cited
2008Cochrane Handbook for Systematic Reviews of Interventions25,045 cited
2010Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up?1,185 cited
2016Epidemiology and Reporting Characteristics of Systematic Reviews of Biomedical Research: A Cross-Sectional Study766 cited
2017Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry733 cited
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2012Deploying an interactive machine learning system in an evidence-based practice center530 cited
2017Living systematic reviews: 2. Combining human and machine effort354 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

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2002Identification of randomized controlled trials in systematic reviews: accuracy and reliability of screening records340 cited

2011Applications of text mining within systematic reviews212 cited

2015Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers184 cited

Cited by

2020An evaluation of DistillerSR’s machine learning-based prioritization tool for title/abstract screening – impact on reviewer-relevant outcomes139 cited
2019Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools133 cited
2020Machine learning for screening prioritization in systematic reviews: comparative performance of Abstrackr and EPPI-Reviewer112 cited
2021Guidance for using artificial intelligence for title and abstract screening while conducting knowledge syntheses104 cited
2023Performance of active learning models for screening prioritization in systematic reviews: a simulation study into the Average Time to Discover relevant records96 cited
2024Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review87 cited
2022Machine learning computational tools to assist the performance of systematic reviews: A mapping review85 cited
2024Performance of a Large Language Model in Screening Citations85 cited
2020The semi-automation of title and abstract screening: a retrospective exploration of ways to leverage Abstrackr’s relevance predictions in systematic and rapid reviews80 cited
2024Screening Smarter, Not Harder: A Comparative Analysis of Machine Learning Screening Algorithms and Heuristic Stopping Criteria for Systematic Reviews in Educational Research74 cited
2024Sensitivity and Specificity of Using GPT-3.5 Turbo Models for Title and Abstract Screening in Systematic Reviews and Meta-analyses66 cited
2021Natural language processing was effective in assisting rapid title and abstract screening when updating systematic reviews64 cited
2023The use of artificial intelligence for automating or semi-automating biomedical literature analyses: A scoping review64 cited
2021Text mining to support abstract screening for knowledge syntheses: a semi-automated workflow63 cited
2020Active learning for screening prioritization in systematic reviews - A simulation study51 cited
2023Can artificial intelligence separate the wheat from the chaff in systematic reviews of health economic articles?50 cited