DenseReviewer: A Screening Prioritisation Tool for Systematic Review based on Dense Retrieval
Journal:
arXiv
Published Date:
Feb 5, 2025
Abstract
Screening is a time-consuming and labour-intensive yet required task for
medical systematic reviews, as tens of thousands of studies often need to be
screened. Prioritising relevant studies to be screened allows downstream
systematic review creation tasks to start earlier and save time. In previous
work, we developed a dense retrieval method to prioritise relevant studies with
reviewer feedback during the title and abstract screening stage. Our method
outperforms previous active learning methods in both effectiveness and
efficiency. In this demo, we extend this prior work by creating (1) a web-based
screening tool that enables end-users to screen studies exploiting
state-of-the-art methods and (2) a Python library that integrates models and
feedback mechanisms and allows researchers to develop and demonstrate new
active learning methods. We describe the tool's design and showcase how it can
aid screening. The tool is available at https://densereviewer.ielab.io. The
source code is also open sourced at https://github.com/ielab/densereviewer.
