ReviewNPJ digital medicine2025
Patient agency and large language models in worldwide encoding of equity.
Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Artificial intelligence in clinical trials-state of the evidence, gaps, and next steps.EClinicalMedicine · 2026Review
- Large language models for tympanostomy patient education: readability and guideline adherence.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Attitudes Toward Large Language Models in Health Care and Preferences for Their Adoption and Oversight Among Health Care Professionals: Cross-Sectional Survey.Journal of medical Internet research · 2026Article
- Implications of the new US AI framework in medicine.Communications medicine · 2026Article
- Evidence, use cases, and implementation safeguards of large language models in primary care.Communications medicine · 2026Review
- Generative AI, foundation models and large language models in radiation therapy physics: Clinical applications, challenges, and future directions.Medical physics · 2026Review
- Total product lifecycle regulatory considerations and recommendations for generative AI-enabled medical devices.European heart journal. Digital health · 2026Article
- A Manifesto for Universal Healthcare: Reconstituting Primary Care Through Digital Innovation, Microbial Technologies and Empowered Citizenship.Microbial biotechnology · 2026Article
- Do world-wide policy initiatives for regulating health care related artificial intelligence safeguard the declaration of Helsinki?EClinicalMedicine · 2026Review
- Ten years on: how far have we come in patient engagement in diagnosis?Diagnosis (Berlin, Germany) · 2025Review
- Implications of integrating large language models into clinical decision making.Communications medicine · 2025Review
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
Abstract
Large language models progressively result in improved ways of patient engagement and access to healthcare, reaching both an exciting and concerning time, as they no longer serve solely as a guide to clinicians, but, for the first time enable patients to make decisions that directly affect their health. We present the benefits and risks of this paradigm-shift in the practice of medicine, that offers the possibility of promoting health equity.
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.