Large language models, updates, and evaluation of automation tools for systematic reviews: a summary of significant discussions at the eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR).

Annette M O'Connor, Justin Clark, James Thomas, Ren�� Spijker, Wojciech Kusa, Vickie R Walker, Melissa Bond
Author Information
  1. Annette M O'Connor: College of Veterinary Medicine, Michigan State University, East Lansing, MI, 48824, USA. oconn445@msu.edu.
  2. Justin Clark: Institute for Evidence-Based Healthcare, Bond University, Robina, QLD, 4226, Australia.
  3. James Thomas: EPPI Centre, UCL Social Research Institute, University College London, London, WC1E 6BT, UK.
  4. Ren�� Spijker: Julius Centre for Health Sciences and Primary Care, Cochrane Netherlands, University Medical Centre Utrecht, University Utrecht, Utrecht, the Netherlands.
  5. Wojciech Kusa: TU Wien, Vienna, Austria.
  6. Vickie R Walker: Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC, USA.
  7. Melissa Bond: EPPI Centre, UCL Social Research Institute, University College London, London, WC1E 6BT, UK.

Abstract

The eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR) was held on September 7 and 8, 2023, at the University College London, London, England. ICASR is an interdisciplinary group whose goal is to maximize the use of technology for conducting rapid, accurate, and efficient evidence synthesis, e.g., systematic reviews, evidence maps, and scoping reviews of scientific evidence. In 2023, the major themes discussed were understanding the benefits and harms of automation tools that have become available in recent years, the advantages and disadvantages of large language models in evidence synthesis, and approaches to ensuring the validity of tools for the proposed task.

Keywords

References

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MeSH Term

Humans
Systematic Reviews as Topic
Automation
Language

Word Cloud

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