ReviewAbdominal radiology (New York)2025
Multi-modal large language models in radiology: principles, applications, and potential.
Review in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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Who cites it
15 citing papers in PubMed.
- Large language models for lumbar spondylolisthesis detection: a multi-center pilot comparative radiographic accuracy study.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2026Article
- [The digital patient journey in radiological emergencies : Massive hemoptysis as a stress test of interoperability].Radiologie (Heidelberg, Germany) · 2026Review
- Benchmarking GPT-5, Gemini 2.5 Pro, Grok 4, and other LLMs on pediatric dentistry questions from a dental specialization exam.Scientific reports · 2026Article
- Diagnostic and localization performance of multimodal large language models in the interpretation of dental periapical radiographs.BMC oral health · 2026Article
- Artificial intelligence in respiratory medicine: From diagnosis to treatment and future directions.Chinese medical journal pulmonary and critical care medicine · 2026Review
- MoE-based multimodal alignment for vocal metaverse classrooms.Scientific reports · 2026Article
- Uncover This Tech Term: Large Vision-Language Models in Radiology.Korean journal of radiology · 2026Article
- Artificial Intelligence in Radiology: Hidden Fragilities and the Path to Resilience.Saudi medical journal · 2026Review
- Diagnostic Accuracy and Stability of Multimodal Large Language Models for Hand Fracture Detection: A Multi-Run Evaluation on Plain Radiographs.Diagnostics (Basel, Switzerland) · 2026Article
- Large Language Model-Based Text Recognition and Structured Data Extraction for Dietary Surveys.China CDC weekly · 2026Article
- Comparative performance of Chinese and international large language models on the Chinese radiology attending physician qualification examination.Scientific reports · 2025Article
- Applications and Future Perspectives of Large Language Models in Otolaryngology-Head and Neck Surgery: A Comprehensive Survey.Clinical and experimental otorhinolaryngology · 2025Review
- Vision-language model for report generation and outcome prediction in CT pulmonary angiogram.NPJ digital medicine · 2025Article
- Enhancing ultrasonographic detection of hepatocellular carcinoma with artificial intelligence: current applications, challenges and future directions.BMJ open gastroenterology · 2025Review
- Large language models in oncology: a review.BMJ oncology · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) and multi-modal large language models (MLLMs) represent the cutting-edge in artificial intelligence. This review provides a comprehensive overview of their capabilities and potential impact on radiology. Unlike most existing literature reviews focusing solely on LLMs, this work examines both LLMs and MLLMs, highlighting their potential to support radiology workflows such as report generation, image interpretation, EHR summarization, differential diagnosis generation, and patient education. By streamlining these tasks, LLMs and MLLMs could reduce radiologist workload, improve diagnostic accuracy, support interdisciplinary collaboration, and ultimately enhance patient care. We also discuss key limitations, such as the limited capacity of current MLLMs to interpret 3D medical images and to integrate information from both image and text data, as well as the lack of effective evaluation methods. Ongoing efforts to address these challenges are introduced.
Indexed as
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39621074What 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.