ArticleJournal of the American Medical Informatics Association : JAMIA2020
Trialstreamer: A living, automatically updated database of clinical trial reports.
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.
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
36 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Large Language Model Analysis of Reporting Quality of Randomized Clinical Trial Articles: A Systematic Review.JAMA network open · 2025Pooled it
- Advances in orofacial pain research: a bibliometric analysis.Frontiers in neurology · 2025Pooled it
- Data extraction methods for systematic review (semi)automation: Update of a living systematic review.F1000Research · 2021Pooled it
- Methodological information extraction from randomized controlled trial publications: a pilot study.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Trial
- Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine.Findings of ACL. ACL · 2026Article
- AI-Assisted Systematic Literature Review of the Economic Burden of Pneumococcal Disease: Development and Validation Study.JMIR AI · 2026Article
- A literature review and reflection on clinical trials: current challenges, future directions, and potential strategies to overcome practical barriers.AME clinical trials review · 2026Article
- Trial Files: Leveraging large language models to summarize practice-changing clinical trials for clinicians.PloS one · 2026Article
- Evidence triangulator: using large language models to extract and synthesize causal evidence across study designs.Nature communications · 2025Article
- Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review.Findings of ACL. ACL · 2025Article
- High-precision information retrieval for rapid clinical guideline updates.NPJ digital medicine · 2025Article
- Digital Tools to Support the Systematic Review Process: An Introduction.Journal of evaluation in clinical practice · 2025Review
- SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications.Scientific data · 2025Article
- SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications.medRxiv : the preprint server for health sciences · 2025Article
- Article
- The Impact of Temperature on Extracting Information From Clinical Trial Publications Using Large Language Models.Cureus · 2024Article
- Artificial intelligence in food and nutrition evidence: The challenges and opportunities.PNAS nexus · 2024Article
- Predicting the sample size of randomized controlled trials using natural language processing.JAMIA open · 2024Article
- Text classification models for assessing the completeness of randomized controlled trial publications based on CONSORT reporting guidelines.Scientific reports · 2024Article
- A question-answering framework for automated abstract screening using large language models.Journal of the American Medical Informatics Association : JAMIA · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
objectiveRandomized controlled trials (RCTs) are the gold standard method for evaluating whether a treatment works in health care but can be difficult to find and make use of. We describe the development and evaluation of a system to automatically find and categorize all new RCT reports. MATERIALS AND
methodsTrialstreamer continuously monitors PubMed and the World Health Organization International Clinical Trials Registry Platform, looking for new RCTs in humans using a validated classifier. We combine machine learning and rule-based methods to extract information from the RCT abstracts, including free-text descriptions of trial PICO (populations, interventions/comparators, and outcomes) elements and map these snippets to normalized MeSH (Medical Subject Headings) vocabulary terms. We additionally identify sample sizes, predict the risk of bias, and extract text conveying key findings. We store all extracted data in a database, which we make freely available for download, and via a search portal, which allows users to enter structured clinical queries. Results are ranked automatically to prioritize larger and higher-quality studies.
resultsAs of early June 2020, we have indexed 673 191 publications of RCTs, of which 22 363 were published in the first 5 months of 2020 (142 per day). We additionally include 304 111 trial registrations from the International Clinical Trials Registry Platform. The median trial sample size was 66.
conclusionsWe present an automated system for finding and categorizing RCTs. This yields a novel resource: a database of structured information automatically extracted for all published RCTs in humans. We make daily updates of this database available on our website (https://trialstreamer.robotreviewer.net).
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.