ASReview: Open Source Software for Efficient and Transparent Active Learning for Systematic Reviews.
Year: 2020
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3037541136