ASReview

Product or Programme · All products and programmes
Evidence · 1 claim (1 for) · 1 study (1 causal), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

ASReview is an open-source machine-learning platform developed for efficient abstract screening in systematic reviews by iteratively prioritizing records for reviewer classification.

Components

• ASReview open-source machine-learning abstract screening software: ASReview is an open-source machine-learning tool for abstract screening in systematic reviews, used in this study's retrospective simulation. The article states that "the ASReview software, an open-source platform, provides multiple learning algorithms for both feature extraction and classification." Researchers install it, load a study database (titles and abstracts), classify a small initial subset, then choose a feature extraction method, classifier, balancing strategy (default dynamic resampling), and query strategy (default certainty-based sampling). The algorithm iteratively suggests the study predicted most relevant for the reviewer's include/exclude decision. (Campos et al. (2024))

Claims

• Active learning algorithms reduce abstract-screening workload in education systematic reviews, saving on average 58% of irrelevant-record screening and 1.66 days at 95% sensitivity [+M]

Related Products and Programmes

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Key Sources

• Campos, D. G., Fütterer, T., Gfrörer, T., Lavelle-Hill, R., Murayama, K., König, L., Hecht, M., Zitzmann, S., & Scherer, R. (2024). Screening Smarter, Not Harder: A Comparative Analysis of Machine Learning Screening Algorithms and Heuristic Stopping Criteria for Systematic Reviews in Educational Research. Educational Psychology Review. https://doi.org/10.1007/s10648-024-09862-5

Page metadata

Field	Value
type	product
id	asreview
title	ASReview
description	ASReview is an open-source machine-learning platform developed for efficient abstract screening in systematic reviews by iteratively prioritizing records for reviewer classification.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-21
trust	unverified — no one has confirmed this page's content

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