AiReview: An Open Platform for Accelerating Systematic Reviews with LLMs
Journal:
arXiv
Published Date:
Apr 5, 2025
Abstract
Systematic reviews are fundamental to evidence-based medicine. Creating one
is time-consuming and labour-intensive, mainly due to the need to screen, or
assess, many studies for inclusion in the review. Several tools have been
developed to streamline this process, mostly relying on traditional machine
learning methods. Large language models (LLMs) have shown potential in further
accelerating the screening process. However, no tool currently allows end users
to directly leverage LLMs for screening or facilitates systematic and
transparent usage of LLM-assisted screening methods. This paper introduces (i)
an extensible framework for applying LLMs to systematic review tasks,
particularly title and abstract screening, and (ii) a web-based interface for
LLM-assisted screening. Together, these elements form AiReview-a novel platform
for LLM-assisted systematic review creation. AiReview is the first of its kind
to bridge the gap between cutting-edge LLM-assisted screening methods and those
that create medical systematic reviews. The tool is available at
https://aireview.ielab.io. The source code is also open sourced at
https://github.com/ielab/ai-review.
