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Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization
5 references·3 citing·33 second hop
Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization (2020)Generating (Factual?) Narrative Summaries…HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case (2019)HISTORIAE, History of Socio-C…Machine learning for identifying Randomized Controlled Trials: An evaluation and practitioner's guide (2018)Machine learning for identify…Automating Biomedical Evidence Synthesis: RobotReviewer (2017)Automating Biomedical Evidenc…RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials (2015)RobotReviewer: evaluation of …An Introduction to Systematic Reviews (2013)An Introduction to Systematic…A foundation model for human-AI collaboration in medical literature mining (2025)A foundation model for human-…Zero‐ and few‐shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials (2024)Zero‐ and few‐shot prompting …Towards Interpretable Mental Health Analysis with Large Language Models (2023)Towards Interpretable Mental …Chapter 8: Assessing risk of bias in included studies (2008)The Cochrane Collaboration's tool for assessing risk of bias in randomised trials (2011)Systematic review automation technologies (2014)Recommendations for assessing the risk of bias in systematic reviews of health-care interventions (2017)Considering bias and conflicts of interest among the included studies (2019)Artificial intelligence and the conduct of literature reviews (2021)Seventy-Five Trials and Eleven Systematic Reviews a Day: How Will We Ever Keep Up? (2010)Systematic reviews: CRD's guidance for undertaking reviews in health care (2010)Fact or Fiction: Verifying Scientific Claims (2020)Machine learning computational tools to assist the performance of systematic reviews: A mapping review (2022)Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review (2024)Improving the Quality of Reporting of Randomized Controlled Trials (1996)Improving the quality of reporting of randomized controlled trials. The CONSORT statement (1996)Cochrane Handbook for Systematic Reviews of Interventions (2010)Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews (2020)A declaração PRISMA 2020: diretriz atualizada para relatar revisões sistemáticas (2022)Artificial intelligence for literature reviews: opportunities and challenges (2024)IEMOCAP: interactive emotional dyadic motion capture database (2008)Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics (2023)Evaluating Risk Progression in Mental Health Chatbots Using Escalating Prompts (2023)Recognizing the Role of ChatGPT in Decision-Making and Recognition of Mental Health Disorders among Entrepreneurs (2024)RoB 2: a revised tool for assessing risk of bias in randomised trials (2019)Human Versus Artificial Intelligence: Comparing Cochrane Authors' and ChatGPT's Risk of Bias Assessments (2025)Role of Generative Artificial Intelligence in Assisting Systematic Review Process in Health Research: A Systematic Review (2025)How to do a meta‐analysis (2010)The Mass Production of Redundant, Misleading, and Conflicted Systematic Reviews and Meta‐analyses (2016)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health (2013)RAMESES publication standards: realist syntheses (2013)Applying GRADE-CERQual to qualitative evidence synthesis findings: introduction to the series (2018)LEGAL-BERT: The Muppets straight out of Law School (2020)On the Opportunities and Risks of Foundation Models (2021)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)
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References

  • 2019HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case16,511 cited
  • 2013An Introduction to Systematic Reviews1,235 cited
  • 2018Machine learning for identifying Randomized Controlled Trials: An evaluation and practitioner's guide433 cited
  • 2015RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials316 cited
  • 2017Automating Biomedical Evidence Synthesis: RobotReviewer96 cited

Cited by

  • 2023Towards Interpretable Mental Health Analysis with Large Language Models155 cited
  • 2024Zero‐ and few‐shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials28 cited
  • 2025A foundation model for human-AI collaboration in medical literature mining28 cited

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