ArticleNPJ cardiovascular health2025
Leveraging large language models to bridge the digital divide in cardiovascular health research.
Article in NPJ cardiovascular health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Design and rationale of the my heart counts cardiovascular health study: a large-scale, fully digital biobank, and randomized trial of large language model-driven coaching of physical activity.American journal of preventive cardiology · 2026Article
- Speaking the Language of Inclusion: Examining English Language Requirements in Cardiovascular Digital Health Trials.JACC. Advances · 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
6 authors.
Funding
Abstract
Advances in digital health exclude Hispanic/Latinx populations with limited English language proficiency, despite their high cardiovascular risk and smartphone usage. Large language models (LLMs) offer promising English-to-Spanish translational solutions, with comparable accuracy to professional medical translators. In this work, we present data and propose a hybrid workflow that combines automated LLM translation with professional review to reduce costs and improve Hispanic/Latinx inclusion in cardiovascular digital health research.
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.