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.
- ASReview LAB Quick Tour
- End-user testing
- Frequently Asked Questions
- Simulation results
- Active learning algorithms
- Command Line Interface (CLI)
- Programming interface (API)
- Develop Extensions
- API Reference
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. arXiv.org, http://arxiv.org/abs/2006.12166.