ASReview: Active learning for Systematic Reviews

ASReview is a project to accelerate the process of systematic reviewing. It is written in python, and uses deep learning to predict which papers should be most likely included in the review. Our software is designed to accelerate the step of screening abstracts and titles with a minimum of papers to be read by a human with no or very few false negatives.

ASReview software implements two different modes:

  • ASReview LAB This modus is used to perform a systematic review with interaction by the reviewer (the ‘oracle’ in literature on active learning). The software presents papers to the reviewer, whereafter the reviewer classifies them.
  • Simulate The simulation modus is used to measure the performance of the active learning software on the results of fully labeled systematic reviews. To use the simulation mode, knowledge on programming and bash/Command Prompt is highly recommanded.

The source code is freely available at GitHub.

Indices and tables


The preprint ArXiv:2006.12166 can be used to cite this project.

van de Schoot, Rens, et al. “ASReview: Open Source Software for Efficient and
Transparent Active Learning for Systematic Reviews.” ArXiv:2006.12166 [Cs],
June 2020.,

For citing the software, please refer to the specific release of the ASReview software on Zenodo DOI. The menu on the right can be used to find the citation format of prevalence.