ArticleStudies in health technology and informatics2025
EvidenceOutcomes: A Dataset of Clinical Trial Publications with Clinically Meaningful Outcomes.
Article in Studies in health technology and informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The fundamental process of evidence extraction in evidence-based medicine relies on identifying PICO elements, with Outcomes being the most complex and often overlooked. To address this, we introduce EvidenceOutcomes, a large annotated corpus of clinically meaningful outcomes. A robust annotation guideline was developed in collaboration with clinicians and NLP experts, and three annotators annotated the Results and Conclusions of 500 PubMed abstracts and 140 EBM-NLP abstracts, achieving an inter-rater agreement of 0.76. A fine-tuned PubMedBERT model achieved F1 scores of 0.69 (entity level) and 0.76 (token level). EvidenceOutcomes offers a benchmark for advancing machine learning algorithms in extracting clinically meaningful outcomes.
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.