Systematic reviews performed within the UU and UMC Utrecht
This dataset contains an overview of 117 systematic reviews published by corresponding authors affiliated to Utrecht University (UU) or UMC Utrecht in 2020.
This dataset contains an overview of 117 systematic reviews published by corresponding authors affiliated to Utrecht University (UU) or UMC Utrecht in 2020.
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.
Explore the systematic review dataset that was used for the publication “Psychological theories of depressive relapse and recurrence” from Brouwer et al., 2019. From pre-processing to the final dataset, a look into the complete systematic review process behind this publication.
Recreate the simulation study on the systematic review of Smid et al.. From pre-processing to the final dataset, dive into the complete process behind this publication.
After manually screening 5050 studies, Smid et al included only 27 studies for their review. In the current study, both the Bayesian and logistic regression models found more than 80% of relevant publications after screening only 10% of all publications.
To determine the defaults we performed a simulation study and Naive Bayes + TF-IDF model performed the best.
Combining human intelligence and machine learning into Researcher-in-the-loop machine learning. An effective technique for training models.
The CORD-19 database is available in ASReview and can be used to search for relevant Corona-related publication using active learning.
ASReview LAB is user-friendly software for exploring the future of AI in systematic reviews. The software implements an Oracle Mode, an Exploration Mode, and a Simulation Mode.