ArticleJournal of medical Internet research2025
Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 3 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
69 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Testing and evaluation of generative large language models in electronic health record applications: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Human researchers are superior to large language models in writing a medical systematic review in a comparative multitask assessment.Scientific reports · 2025Pooled it
- Artificial intelligence in ADHD: a global perspective on research hotspots, trends and clinical applications.Frontiers in human neuroscience · 2025Pooled it
- Misaligned by design: evaluating and deploying generative AI for the real-world conditions of primary care: a Nordic and European perspective.Scandinavian journal of primary health care · 2026Article
- Large language model-based triage to identify antiretroviral therapy adherence barriers and risk levels in patient messages.JAMIA open · 2026Article
- Frameworks, Methodologies, and Tools for Evaluating Large Language Models in Digital Mental Health Interventions: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- Exploring Bias in Medical Applications of Large Language Models: Protocol for a Systematic Review.JMIR research protocols · 2026Article
- Stepwise Diagnostic Evaluation of Chinese Large Language Models: Comparative Study of Common and Rare Diseases.Journal of medical Internet research · 2026Article
- An automatic consult reply system for therapeutic plasma exchange using retrieval-augmented generation.Vox sanguinis · 2026Article
- Illusion of competence: vision-language models provide confident but inaccurate explanations in cytological diagnostics.Scientific reports · 2026Article
- Human-in-the-Loop as a Safety Guardrail: Clinical Accountability in the Large Language Model Era.Journal of medical Internet research · 2026Article
- Large language models for acute coronary syndrome triage at first medical contact in emergency departments.NPJ digital medicine · 2026Article
- Beyond classical models: LLM-driven survival analysis for breast cancer prognosis using European cancer registry data.BMC medical informatics and decision making · 2026Article
- Evaluation of ChatGPT-4o in Breast Cancer Screening: Insights from the 5th Edition BI-RADS Atlas and ACR Guidelines.Journal of imaging informatics in medicine · 2026Article
- Article
- The Performance of DeepSeek R1 and Gemini 3 in Complex Medical Scenarios: Comparative Study.JMIRx med · 2026Article
- The Potential Role of Large Language Models in Assisting Patients and Guiding Emergency Care Visits.Journal of clinical medicine · 2026Article
- Development and prospective shadow evaluation of a domain-specific large language model for emergency neurological diagnosis.NPJ digital medicine · 2026Article
- Interpretable depressive symptoms screening via statistical reasoning-augmented large language models using wearable and environmental data.Scientific reports · 2026Article
- SPOT THE BOT: A comparative quality assessment of AI-generated written instructions for lung ultrasound training.The ultrasound journal · 2026Article
9 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) are rapidly advancing medical artificial intelligence, offering revolutionary changes in health care. These models excel in natural language processing (NLP), enhancing clinical support, diagnosis, treatment, and medical research. Breakthroughs, like GPT-4 and BERT (Bidirectional Encoder Representations from Transformer), demonstrate LLMs' evolution through improved computing power and data. However, their high hardware requirements are being addressed through technological advancements. LLMs are unique in processing multimodal data, thereby improving emergency, elder care, and digital medical procedures. Challenges include ensuring their empirical reliability, addressing ethical and societal implications, especially data privacy, and mitigating biases while maintaining privacy and accountability. The paper emphasizes the need for human-centric, bias-free LLMs for personalized medicine and advocates for equitable development and access. LLMs hold promise for transformative impacts in health care.
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.