ArticleJAMIA open2025
Using artificial intelligence to expedite and enhance plain language summary abstract writing of scientific content.
Article in JAMIA open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Enhancing the quality and trustworthiness of large language model-generated summaries of clinical oncology literature.JAMIA open · 2026Article
- "Now you're talking my language" - Improving health literacy and patient-directed knowledge of scientific abstracts through provision of plain language summaries created by artificial intelligence: A cross sectional infodemiology study.The Ulster medical journal · 2025Article
- Lowering the Barrier to Surgical Research: Can Artificial Intelligence (AI) Support Trainees?ANZ journal of surgeryArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To assess the capacity of a bespoke artificial intelligence (AI) process to help medical writers efficiently generate quality plain language summary abstracts (PLSAs). Materials and Methods: Three independent studies were conducted. In Studies 1 and 3, original scientific abstracts (OSAs; Results: In Study 1, bespoke AI PLSAs were easier to read than medical writer PLSAs across all readability metrics ( Discussion: The bespoke AI process may enhance access to health information by helping medical writers produce PLSAs of scientific content that are fit for purpose. Conclusion: The bespoke AI process can more efficiently create better quality, more readable first draft PLSAs versus medical writer-generated PLSAs.
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.