SynthesisFrontiers in digital health2025
A systematic review of ethical considerations of large language models in healthcare and medicine.
Synthesis in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 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
19 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Application of Large Language Models in Chronic Disease Care: Mixed Methods Systematic Review and Thematic Synthesis.Journal of medical Internet research · 2026Pooled it
- Concerns of Using Large Language Models in Health Care Research and Practice: Umbrella Review.Journal of medical Internet research · 2026Pooled it
- A bibliometric analysis of large language models in mental health research.Frontiers in psychiatry · 2026Pooled it
- Large language models in healthcare: applications, evaluation frameworks, and governance pathways - a scoping review and multidimensional framework.Frontiers in digital health · 2026Pooled it
- A Secure, Scalable Large Language Model-Based System (CIDER) for High-Throughput Clinical Data Extraction From Medical Reports: Retrospective Validation Study.Journal of medical Internet research · 2026Article
- Large language models and large multimodal models in radiology: opportunities, challenges, and the path toward sustainable long-term clinical integration.Japanese journal of radiology · 2026Review
- The Continuity Trap in Data Science Health Research.Journal of medical Internet research · 2026Article
- Evaluation of large language models in root resorption scenarios: an ESE-aligned comparative performance assessment.Odontology · 2026Article
- Ethical Governance of Large Language Models in Health Care: Trust, Responsibility, and Equity in Routine Use.Journal of medical Internet research · 2026Article
- Governing Generative AI in Healthcare: A Normative Conceptual Framework for Epistemic Authority, Trust, and the Architecture of Responsibility.Healthcare (Basel, Switzerland) · 2026Article
- Applications of Artificial Intelligence and Smart Devices in Metabolic Dysfunction-associated Steatotic Liver Disease.Journal of clinical and translational hepatology · 2026Article
- Feasibility of a multi-metric framework for evaluating patient-facing AI communication in cosmetic dentistry: an exploratory proof-of-concept study.Frontiers in oral health · 2026Article
- Hotspot Evolution and Future Prospects of Large Language Models in Medical Education: A Bibliometric Analysis.Advances in medical education and practice · 2026Article
- Clinical nursing interns' perceptions of artificial intelligence-assisted tools in human-AI collaboration: a qualitative persona-based study.Frontiers in public health · 2026Article
- The double-edged sword of generative AI in dermatology: a multi-component cross-sectional study on physician burnout, patient satisfaction, and communication quality.Frontiers in medicine · 2026Article
- Acceptance of generative AI-assisted medical decision-making among Chinese physicians and patients and its ethical determinants: a cross-sectional survey.Frontiers in public health · 2026Article
- Large language models in patient education for brain tumors: opportunities, risks, and ethical considerations.Frontiers in oncology · 2026Review
- The AI Health Arms Race: A Critical Perspective on Big Tech and the Widening Global Health Equity Gap.Journal of multidisciplinary healthcare · 2026Article
- Large language model bias auditing for periodontal diagnosis using an ambiguity-probe methodology: a pilot study.Frontiers in digital health · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid integration of large language models (LLMs) into healthcare offers significant potential for improving diagnosis, treatment planning, and patient engagement. However, it also presents serious ethical challenges that remain incompletely addressed. In this review, we analyzed 27 peer-reviewed studies published between 2017 and 2025 across four major open-access databases using strict eligibility criteria, robust synthesis methods, and established guidelines to explicitly examine the ethical aspects of deploying LLMs in clinical settings. We explore four key aspects, including the main ethical issues arising from the use of LLMs in healthcare, the prevalent model architectures employed in ethical analyses, the healthcare application domains that are most frequently scrutinized, and the publication and bibliographic patterns characterizing this literature. Our synthesis reveals that bias and fairness (
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.