Transparent Reporting of AI in Systematic Literature Reviews: Development of the PRISMA-trAIce Checklist
PRISMA-trAIce establishes an important framework to improve the transparency and methodological integrity of AI-assisted systematic reviews, enhancing the trust required for the responsible application of AI-assisted systematic reviews in evidence synthesis. We present this work as a foundational proposal, explicitly inviting the scientific community to join an open science process of consensus building. Through this collaborative refinement, we aim to evolve PRISMA-trAIce into a formally endorsed guideline, thereby ensuring the collective validation and scientific rigor of future AI-driven research.
Authors
- Thorsten Schüppstuhl (ORCID: https://orcid.org/0000-0002-9616-3976)
- Keno Moenck (ORCID: https://orcid.org/0000-0003-3892-1588)
- Julian Koch (ORCID: https://orcid.org/0000-0003-3700-6425)
- Ole Schmedemann (ORCID: https://orcid.org/0000-0001-6488-5141)
- Dirk Holst (ORCID: https://orcid.org/0000-0001-9918-349X)
Institutions
- Universität Hamburg (DE)
- Hamburg University of Technology (DE)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-10-12
- DOI
- https://doi.org/10.2196/80247
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31
Funders
- DeepMind