ArticleFamily medicine and community health2024
Potential applications and implications of large language models in primary care.
Article in Family medicine and community health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.
What it found
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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
38 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Unveiling the Potential of Large Language Models in Transforming Chronic Disease Management: Mixed Methods Systematic Review.Journal of medical Internet research · 2025Pooled it
- Optimizing generative artificial intelligence for clinical summarization: a blinded comparison study of automated versus human care planning synopses.JAMIA open · 2026Article
- Evidence, use cases, and implementation safeguards of large language models in primary care.Communications medicine · 2026Review
- AI-Based Diagnostic Platform Capabilities With Lyme Disease as a Use Case: Integrative Exploration.Online journal of public health informatics · 2026Article
- Exploring the Role of Large Language Models in Primary Care: Qualitative Study of Physicians in the United States and the Netherlands.JMIR medical informatics · 2026Article
- Current state of electronic problems lists in primary care: a rapid scoping review.Family practice · 2026Article
- Evaluation of AI tool assisting primary healthcare physicians to diagnostic and treatment tasks.Family medicine and community health · 2026Article
- Use of Generative Artificial Intelligence in the Management of Low Back Pain: a Scoping Review.Journal of medical systems · 2026Article
- Article
- Evaluating large language model usage for calculating readability of patient education materials in ophthalmology.Eye (London, England) · 2026Article
- Large Language Models and Primary Care: A Scoping Review.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Feasibility of a generative AI chatbot to support breastfeeding in the Brazilian Unified National Health System.Cadernos de saude publica · 2026Article
- Artificial Intelligence in Outpatient Primary Care: A Scoping Review on Applications, Challenges, and Future Directions.Journal of general internal medicine · 2026Article
- The use of artificial intelligence in healthcare as perceived by the citizens and patients: a narrative review of the literature.European journal of public health · 2025Review
- Empowering standardized residency training in China through large language models: problem analysis and solutions.Annals of medicine · 2025Article
- Generative AI Chatbot for Diabetes Management: Formative 2-Part Qualitative Study Using DTalksBot Involving Patients and Clinicians.JMIR formative research · 2025Article
- A Meta-Analysis of ChatGPT's Performance on Dermatology Specialty-Level (Board-Style) Certification Questions.Indian dermatology online journal · 2025Article
- Challenges of Implementing LLMs in Clinical Practice: Perspectives.Journal of clinical medicine · 2025Article
- Comparing artificial intelligence- vs clinician-authored summaries of simulated primary care electronic health records.JAMIA open · 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical practice, including in health and healthcare. The potential applications of LLM-based programmes in the medical field range from assisting medical practitioners in improving their clinical decision-making and streamlining administrative paperwork to empowering patients to take charge of their own health. However, despite the broad range of benefits, the use of such AI tools also comes with several limitations and ethical concerns that warrant further consideration, encompassing issues related to privacy, data bias, and the accuracy and reliability of information generated by AI. The focus of prior research has primarily centred on the broad applications of LLMs in medicine. To the author's knowledge, this is, the first article that consolidates current and pertinent literature on LLMs to examine its potential in primary care. The objectives of this paper are not only to summarise the potential benefits, risks and challenges of using LLMs in primary care, but also to offer insights into considerations that primary care clinicians should take into account when deciding to adopt and integrate such technologies into their clinical practice.
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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.