ArticleiScience2025
Artificial intelligence as team member versus manual screening to conduct systematic reviews in medical sciences.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Methods in Systematic Reviews of Health Economic Evaluations in Submissions to Health Technology Assessment Agencies: How Systematic Are They, and Does This Matter?PharmacoEconomics · 2026Review
- Artificial Intelligence Resources for the Screening of Titles and Abstracts in Systematic Reviews: A Scoping Review.Cochrane evidence synthesis and methods · 2026Review
- Leveraging prompt-driven generative AI for systematic reviews in digital psychiatry: A stage-matched comparative proof-of-concept for healthcare researchers and clinicians.PLOS digital health · 2026Article
- Screenathon 2.0: human-AI collaborative screening applied to patient-generated health data.Scientific reports · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systematic reviews require substantial time and effort. This study compared the results of conducting reviews by human reviewers with those conducted with Artificial Intelligence (AI). We identified 11 AI tools that could assist in conducting a systematic review. None of the AI tools could retrieve all articles that were detected with a manual search strategy. We identified tools for deduplication but did not evaluate them. AI screening tools assist the human reviewer in presenting the most relevant article on top, which could reduce the number of articles that need to be screened on title and abstract, and on full text. There was a poor inter-rater reliability to evaluate the risk of bias between AI tools and the human reviewers. A summary table created by AI tools differs substantially from manually constructed summary tables. This study highlights the potential of AI tools to support systematic reviews, particularly during screening phases, but not to replace human reviews.
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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.