ReviewCommunications medicine2023
The future landscape of large language models in medicine.
Review in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07500428 (Construction of a Standardized Benchmark Evaluation System for Intelligent Breast Ultrasound Image Interpretation and Systematic Performance Assessment of Multimodal Artificial Intelligence Models Based on ACR BI-RADS v2025 Criteria), which is not on this map. Cited by 500 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.
Construction of a Standardized Benchmark Evaluation System for Intelligent Breast Ultrasound Image Interpretation and Systematic Performance Assessment of Multimodal Artificial Intelligence Models Based on ACR BI-RADS v2025 Criteria
Who cites it
500 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Communication and medical errors: a bibliometric analysis of research trends and knowledge structures.Frontiers in medicine · 2026Pooled it
- Pooled it
- An LLM chatbot to facilitate primary-to-specialist care transitions: a randomized controlled trial.Nature medicine · 2026Trial
- A large language model for complex cardiology care.Nature medicine · 2026Trial
- 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
- Bias and Reliability of AI-Based Peer Review: A Comparative Study of ChatGPT and Claude Evaluating Scientific Abstracts.Journal of general internal medicine · 2026Article
- Can large language models accurately compute descriptive statistics from structured datasets? A comparative evaluation of ChatGPT and Claude.American heart journal plus : cardiology research and practice · 2026Article
- A tailored maturity model for REDCap-based patient-facing technology: revealing development stages and guiding future evolution.JAMIA open · 2026Review
- Performance of large language models on the Japanese cardiovascular surgery board examination: a comparative analysis of eight contemporary AI models with educational implications.General thoracic and cardiovascular surgery · 2026Article
- Attitudes Toward Large Language Models in Health Care and Preferences for Their Adoption and Oversight Among Health Care Professionals: Cross-Sectional Survey.Journal of medical Internet research · 2026Article
- Review
- "Small" Large Language Models in the Hospital: Evaluation Study on Real-World Data in a Resource-Constrained Setting.Journal of medical Internet research · 2026Article
- Atherosclerosis prediction with large language models via prompt engineering.Journal of human hypertension · 2026Article
- Overcoming barriers to neurosurgical care with technology and innovation.BMC global and public health · 2026Review
- A pragmatic risk-stratified framework for using large language models in intensive care medicine: A narrative review.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2026Review
- Integration of large language models and evidence-based Chinese medicine: A scoping review.Integrative medicine research · 2026Review
- Artificial intelligence in clinical genetics: Current practice and attitudes among the clinical genetics workforce.Genetics in medicine : official journal of the American College of Medical Genetics · 2026Article
- Clinical decision support in hematological malignancies using a case-grounded AI agent.Nature medicine · 2026Article
- Assessing the performance of three large language models in thyroid cancer tumour board decision-making.Updates in surgery · 2026Article
440 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
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and generate text. LLMs attracted substantial public attention after OpenAI's ChatGPT was made publicly available in November 2022. LLMs can often answer questions, summarize, paraphrase and translate text on a level that is nearly indistinguishable from human capabilities. The possibility to actively interact with models like ChatGPT makes LLMs attractive tools in various fields, including medicine. While these models have the potential to democratize medical knowledge and facilitate access to healthcare, they could equally distribute misinformation and exacerbate scientific misconduct due to a lack of accountability and transparency. In this article, we provide a systematic and comprehensive overview of the potentials and limitations of LLMs in clinical practice, medical research and medical education.
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.