Package: asreview
ASReview: Active learning for Systematic ReviewsSystematically screening large amounts of textual data is time-consuming and
often tiresome. The rapidly evolving field of Artificial Intelligence (AI) has
allowed the development of AI-aided pipelines that assist in finding relevant
texts for search tasks. A well-established approach to increasing efficiency
is screening prioritization viaActive
Learning.The Active learning for Systematic Reviews (ASReview) project, published inNature Machine Intelligenceimplements different machine learning algorithms that interactively query the
researcher. ASReview LAB  is designed to accelerate the step of screening
textual data with a minimum of records to be read by a human with no or very
few false negatives. ASReview LAB will save time, increase the quality of
output and strengthen the transparency of work when screening large amounts of
textual data to retrieve relevant information. Active Learning will support
decision-making in any discipline or industry.ASReview software implements three different modes:OracleScreen textual data in
interaction with the active learning model. The reviewer is the 'oracle',
making the labeling decisions.ExplorationExplore or
demonstrate ASReview LAB with a completely labeled dataset. This mode is
suitable for teaching purposes.SimulationEvaluate
the performance of active learning models on fully labeled data. Simulations
can be run in ASReview LAB or via the command line interface with more
advanced options.InstallationThe ASReview software requires Python 3.8 or later. Detailed step-by-step
instructions to install Python and ASReview are available forWindowsandmacOSusers.pipinstallasreviewUpgrade ASReview with the following command:pipinstall--upgradeasreviewTo install ASReview LAB with Docker, seeInstall with Docker.How it worksGetting startedGetting Started with ASReview
LAB.CitationIf you wish to cite the underlying methodology of the ASReview software,
please use the following publication in Nature Machine Intelligence:van de Schoot, R., de Bruin, J., Schram, R. et al. An open source machine
learning framework for efficient and transparent systematic reviews.
Nat Mach Intell 3, 125–133 (2021).https://doi.org/10.1038/s42256-020-00287-7For citing the software, please refer to the specific release of
the ASReview software on Zenodohttps://doi.org/10.5281/zenodo.3345592. The menu on the
right can be used to find the citation format of prevalence.For more scientific publications on the ASReview software, go toasreview.ai/papers.ContactFor an overview of the team working on ASReview, seeASReview Research Team.
ASReview LAB is maintained byJonathan de BruinandYongchao Terry Ma.The best resources to find an answer to your question or ways to get in
contact with the team are:Documentation -asreview.readthedocs.ioNewsletter -asreview.ai/newsletter/subscribeQuick tour -ASReview LAB quick tourIssues or feature requests -ASReview issue trackerFAQ -ASReview DiscussionsDonation -asreview.ai/donateContact -asreview@uu.nlLicenseThe ASReview software has an Apache 2.0LICENSE. The ASReview team
accepts no responsibility or liability for the use of the ASReview tool or any
direct or indirect damages arising out of the application of the tool.