ArticleCochrane evidence synthesis and methods2025
Comparison of Elicit AI and Traditional Literature Searching in Evidence Syntheses Using Four Case Studies.
Article in Cochrane evidence synthesis and methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- 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
- Reframing Substance Misuse Prevention: a RE-AIM Analysis of Federal Infrastructure and Future Directions.Prevention science : the official journal of the Society for Prevention Research · 2026Article
- Information Specialist Roles in the Era of Large Language Models: Prompting Continued Professional Development.Campbell systematic reviews · 2026Article
- Evaluating Elicit's systematic reviews workflow in an umbrella review on air pollution and acute lower respiratory infections: a methodological study for quality appraisal.BMC medical research methodology · 2026Article
- Characterizing core outcomes of responsible stewardship for human genomic data in the cloud.BMC medical genomics · 2026Article
- Towards an AI biomedical scientist: Accelerating discoveries in neurodegenerative disease.The journal of prevention of Alzheimer's disease · 2025Article
- Comparison of Elicit AI and Traditional Literature Searching in Evidence Syntheses Using Four Case Studies.Cochrane evidence synthesis and methods · 2025Article
- Exploring the Role of Artificial Intelligence in Evidence Synthesis: Insights From the CORE Information Retrieval Forum 2025.Cochrane evidence synthesis and methods · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Elicit AI aims to simplify and accelerate the systematic review process without compromising accuracy. However, research on Elicit's performance is limited. Objectives: To determine whether Elicit AI is a viable tool for systematic literature searches and title/abstract screening stages. Methods: We compared the included studies in four evidence syntheses to those identified using the subscription-based version of Elicit Pro in Review mode. We calculated sensitivity, precision and observed patterns in the performance of Elicit. Results: The sensitivity of Elicit was poor, averaging 39.5% (25.5-69.2%) compared to 94.5% (91.1-98.0%) in the original reviews. However, Elicit identified some included studies not identified by the original searches and had an average of 41.8% precision (35.6-46.2%) which was higher than the 7.55% average of the original reviews (0.65-14.7%). Discussion: At the time of this evaluation, Elicit did not search with high enough sensitivity to replace traditional literature searching. However, the high precision of searching in Elicit could prove useful for preliminary searches, and the unique studies identified mean that Elicit can be used by researchers as a useful adjunct. Conclusion: Whilst Elicit searches are currently not sensitive enough to replace traditional searching, Elicit is continually improving, and further evaluations should be undertaken as new developments take place.
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What Socratic 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 Socratic graph.