ArticleJournal of clinical and translational science2025
Machine-learning assisted screening for evidence synthesis: Methodological case study of the ASReview tool.
Article in Journal of clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Artificial Intelligence Resources for the Screening of Titles and Abstracts in Systematic Reviews: A Scoping Review.Cochrane evidence synthesis and methods · 2026Review
- Performance of Two AI Approaches in ASReview Compared With Manual Screening for Dementia Care Literature Screening: Comparative Analysis.JMIR formative research · 2026Article
- Rationale and Design of the Cancer Immunotherapy Evidence Living (CIEL) Library: A Continuously Updated Clinical Trial Database of Cancer Immunotherapies.Health science reports · 2026Article
- Network Meta-Analysis and Umbrella Review: Complementary, Not Competing, Tools of Evidence Synthesis.Cureus · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ASReview is a software that can potentially reduce the workload of literature screening in systematic reviews by ranking the retrieved records. We assessed the tool's feasibility, advantages, and limitations, to populate a database of cancer immunotherapy trials. ASReview is easy to use, and it efficiently identified relevant records. It may save resources compared to traditional systematic reviews using two human reviewers. Predefined procedures are necessary to maintain a transparent and reproducible workflow. Limitations include that adding references to existing projects is difficult and that the algorithm learns from every decision, even when this may not be appropriate.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.