Transparent Reporting of AI in Systematic Literature Reviews: Development of the PRISMA-trAIce Checklist.

ABSTRACT:

Background

Systematic literature reviews (SLRs) build the foundation for evidence synthesis, but they are exceptionally demanding in terms of time and resources. While recent advances in artificial intelligence (AI), particularly large language models, offer the potential to accelerate this process, their use introduces challenges to transparency and reproducibility. Reporting guidelines such as the PRISMA-AI (Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Artificial Intelligence Extension) primarily focus on AI as a subject of research, not as a tool in the review process itself.

Objective

To address the gap in reporting standards, this study aimed to develop and propose a discipline-agnostic checklist extension to the PRISMA 2020 statement. The goal was

SUBMITTER: Holst D 

PROVIDER: S-EPMC12694947 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature