ReviewPLOS digital health2024
Large language models in medicine: A review of current clinical trials across healthcare applications.
Review in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- A large language model for complex cardiology care.Nature medicine · 2026Trial
- Beyond one-size-fits-all: mapping information-seeking and decision-making pathways in cancer care.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Statistical Analysis of the Performance of Open-Access Language Models: A Tool in the Clinical Laboratory.EJIFCC · 2026Article
- ChatNSG: An Overview of Contemporary and Emerging Artificial Intelligence Models for the Neurosurgeon.Journal of neurological surgery. Part B, Skull base · 2026Article
- Generative AI, foundation models and large language models in radiation therapy physics: Clinical applications, challenges, and future directions.Medical physics · 2026Review
- Large language models for acute coronary syndrome triage at first medical contact in emergency departments.NPJ digital medicine · 2026Article
- Feasibility and user evaluation of HopeBot: An LLM-powered conversational chatbot for depression screening.PLOS digital health · 2026Article
- Self-regulating the use of large language models in clinical practice: a risk-stratified approach.BMJ health & care informatics · 2026Article
- A systematic review of the limitations of large language models in generating healthcare content.PLOS digital health · 2026Article
- Applications of Large Language Models in Medical Research: From Systematic Reviews to Clinical Studies.Bioengineering (Basel, Switzerland) · 2026Review
- AI knowledge, attitudes, perceptions, and willingness to use AI among oncologists in China: a nationwide cross-sectional study.BMC medical education · 2026Article
- Large language models in healthcare quality management: a European perspective on process automation and compliance.Frontiers in digital health · 2026Review
- Navigating the complexity of WHO CNS5: the evolutionary trajectory of glioma classification and the emergence of large language models.Frontiers in oncology · 2026Review
- Comparative feasibility of reasoning and non-reasoning large language models for gynecologic cancer emergency care.BMC health services research · 2025Article
- Large language models and global health equity: a roadmap for equitable adoption in LMICs.The Lancet regional health. Western Pacific · 2025Review
- When investigator meets large language models: a qualitative analysis of cancer patient decision-making journeys.NPJ digital medicine · 2025Article
- Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification.NPJ precision oncology · 2025Article
- Large language models in clinical nutrition: an overview of its applications, capabilities, limitations, and potential future prospects.Frontiers in nutrition · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review analyzes current clinical trials investigating large language models' (LLMs) applications in healthcare. We identified 27 trials (5 published and 22 ongoing) across 4 main clinical applications: patient care, data handling, decision support, and research assistance. Our analysis reveals diverse LLM uses, from clinical documentation to medical decision-making. Published trials show promise but highlight accuracy concerns. Ongoing studies explore novel applications like patient education and informed consent. Most trials occur in the United States of America and China. We discuss the challenges of evaluating rapidly evolving LLMs through clinical trials and identify gaps in current research. This review aims to inform future studies and guide the integration of LLMs into clinical practice.
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.