ReviewNature medicine2023
Large language models in medicine.
Review in Nature medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,567 papers, 5 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
1,567 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Evidence and Future Directions for Pediatric Health Care Chatbots: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Adaptation of Language Models for Clinical Decision-Making in Health Care: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Improvement of Clinical Practice Guideline Appraisal by Human Experts and AI Agents by Using Structured Guidance: Systematic Review, Meta-Analysis, and Validation Study.Journal of medical Internet research · 2026Pooled it
- Performance of Natural Language Processing Model in Extracting Information from Free-Text Radiology Reports: A Systematic Review and Meta-Analysis.Journal of imaging informatics in medicine · 2026Pooled it
- Generative large language models in the clinical management of Alzheimer's disease and mild cognitive impairment.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- Rethinking Pediatric Asthma Education Through Large Language Model Generation and Simplification: Randomized Double-Blind Study.Journal of medical Internet research · 2026Trial
- Patient experience and psychologists' attitudes toward AI in psychological treatment: A topic-modeling study.Internet interventions · 2026Article
- 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
- CURENet: combining unified representations for efficient chronic disease prediction.Health information science and systems · 2026Article
- Use of Artificial Intelligence in obtaining canine diets: nutritional inadequacy and the need for technical knowledge.Veterinary and animal science · 2026Article
- Assessing the clinical applicability of large language models for microwave ablation guidance.European journal of radiology open · 2026Article
- Application of artificial intelligence in head and neck squamous cell carcinoma.Annals of medicine · 2026Review
- Accuracy of general-purpose large language models (LLMS) in interpreting adolescent idiopathic scoliosis radiographs: a comparative study with experienced spine surgeons.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Associations between parental generative artificial intelligence health-advice use and child vaccination uptake in Japan: an exploratory cross-sectional study.World journal of pediatrics : WJP · 2026Article
- Comparative Evaluation of Large Language Models in the Recognition of Postoperative Complications Following Aesthetic Surgery.Aesthetic plastic surgery · 2026Article
- Evaluation of DeepSeek with a RAG-based knowledge base in preoperative assessment for arthroplasty to improve the decision-making accuracy of junior physicians.Arthroplasty (London, England) · 2026Article
- LLM4PDA: Augmenting piRNA-Disease Association Prediction with Large Language Models.Interdisciplinary sciences, computational life sciences · 2026Article
- A Patient Simulation Framework for Risk Assessment of Conversational Health Care AI: Development and Evaluation Study.JMIR AI · 2026Article
- Article
- Assessing the performance of large language models when used to determine ASA status of cats and dogs and generate anaesthetic protocols.The Veterinary record · 2026Article
1,507 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare settings. ChatGPT is a generative artificial intelligence (AI) chatbot produced through sophisticated fine-tuning of an LLM, and other tools are emerging through similar developmental processes. Here we outline how LLM applications such as ChatGPT are developed, and we discuss how they are being leveraged in clinical settings. We consider the strengths and limitations of LLMs and their potential to improve the efficiency and effectiveness of clinical, educational and research work in medicine. LLM chatbots have already been deployed in a range of biomedical contexts, with impressive but mixed results. This review acts as a primer for interested clinicians, who will determine if and how LLM technology is used in healthcare for the benefit of patients and practitioners.
Indexed as
Identifiers
37460753What 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.