• Corpus ID: 219966056

ASReview: Open Source Software for Efficient and Transparent Active Learning for Systematic Reviews

@article{Schoot2020ASReviewOS,
  title={ASReview: Open Source Software for Efficient and Transparent Active Learning for Systematic Reviews},
  author={Rens van de Schoot and Jonathan de Bruin and Raoul Schram and Parisa Zahedi and Jan de Boer and Felix Weijdema and Bianca Kramer and Martijn Huijts and Maarten Hoogerwerf and Gerbrich Ferdinands and Albert Harkema and Joukje Willemsen and Yongchao Ma and Qixiang Fang and Lars G Tummers and Daniel L. Oberski},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.12166}
}

• R. Schoot, J. D. Bruin, +13 authors D. Oberski
• Published 22 June 2020
• Computer Science
• ArXiv

For many tasks -- including guideline development for medical doctors and systematic reviews for research fields -- the scientific literature needs to be checked systematically. The current practice is that scholars and practitioners screen thousands of studies by hand to find which studies to include in their review. This is error prone and inefficient. We therefore developed an open source machine learning (ML)-aided pipeline: Active learning for Systematic Reviews (ASReview). We show that by using active learning, ASReview can lead to far more efficient reviewing than manual reviewing, while exhibiting adequate quality. Furthermore, the presented software is fully transparent and open source.