Evaluating the effectiveness of large language models in abstract screening: a comparative analysis
While LLM tools are not yet ready to completely replace human experts in abstract screening, they show great promise in revolutionizing the process. They can serve as autonomous AI reviewers, contribute to collaborative workflows with human experts, and integrate with hybrid approaches to develop custom tools for increased efficiency. As technology continues to advance, LLMs are poised to play an increasingly important role in abstract screening, reshaping the workflow of systematic review and meta-analysis studies.
Authors
- Xianming Tan (ORCID: https://orcid.org/0000-0002-5478-2269)
- Michael Li (ORCID: https://orcid.org/0000-0003-0153-8518)
- Jian‐Ping Sun (ORCID: https://orcid.org/0009-0001-7473-1696)
Institutions
- University of North Carolina at Chapel Hill (US)
- University of North Carolina at Greensboro (US)
Publication Details
- Journal
- Systematic Reviews
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1186/s13643-024-02609-x
- Citations
- 87
- Primary Topic
- Meta-analysis and systematic reviews
- Type
- article
- Field-Weighted Citation Impact
- 40.13