High-performance automated abstract screening with large language model ensembles.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 40119675

Abstract

OBJECTIVE: screening is a labor-intensive component of systematic review involving repetitive application of inclusion and exclusion criteria on a large volume of studies. We aimed to validate large language models (LLMs) used to automate abstract screening.

Authors

  • Rohan Sanghera
    Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, United Kingdom.
  • Arun James Thirunavukarasu
    University of Cambridge School of Clinical Medicine Cambridge UK.
  • Marc El Khoury
    School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SP, United Kingdom.
  • Jessica O'Logbon
    GKT School of Medical Education, King's College London, London WC2R 2LS, United Kingdom.
  • Yuqing Chen
    School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SP, United Kingdom.
  • Archie Watt
    Oxford Medical School, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, United Kingdom.
  • Mustafa Mahmood
    UCL Medical School, University College London, London WC1E 6DE, United Kingdom.
  • Hamid Butt
    School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SP, United Kingdom.
  • George Nishimura
    School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SP, United Kingdom.
  • Andrew A S Soltan
    Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, United Kingdom.

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