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Automating Biomedical Evidence Synthesis: RobotReviewer

Iain James Marshall · Joël Kuiper · Byron Wallace

96 citations0/0 files storedAnnual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL Demo)

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Meta-analysis and systematic reviews Biomedical Text Mining and Ontologies Advanced Text Analysis Techniques

Abstract

, an open-source web-based system that uses machine learning and NLP to semi-automate biomedical evidence synthesis, to aid the practice of Evidence-Based Medicine. RobotReviewer processes full-text journal articles (PDFs) describing randomized controlled trials (RCTs). It appraises the reliability of RCTs and extracts text describing key trial characteristics (e.g., descriptions of the population) using novel NLP methods. RobotReviewer then automatically generates a report synthesising this information. Our goal is for RobotReviewer to automatically extract and synthesise the full-range of structured data needed to inform evidence-based practice.

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References

2011The Cochrane Collaboration's tool for assessing risk of bias in randomised trials 2010Systematic reviews: CRD's guidance for undertaking reviews in health care 2010Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up?2015A scoping review of rapid review methods 2017Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry 2015RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials 1999Estimating Time to Conduct a Meta-analysis From Number of Citations Retrieved

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