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Updated: Jul 15, 2025
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
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Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
Tugba Akinci D'Antonoli1, Arnaldo Stanzione2, Christian Bluethgen3
1Cantonal Hospital Baselland, Institute of Radiology and Nuclear Medicine, Liestal, Switzerland
Diagnostic and Interventional Radiology (Ankara, Turkey)
|October 4, 2023
Summary
Large language models (LLMs) are revolutionizing medicine and radiology. This review covers LLM basics, applications, and risks for radiologists to safely adopt this AI technology.
Area of Science:
- Artificial Intelligence in Medicine
- Radiology Informatics
Background:
- The rapid advancement of artificial intelligence (AI), particularly large language models (LLMs), presents new opportunities and challenges in medical fields.
- An increasing volume of research is exploring the integration of LLMs within radiology.
Conclusions:
- Radiologists need to understand LLM fundamentals, applications, and associated risks for safe and effective implementation.
- Familiarity with LLMs is crucial for navigating the future of AI in radiology.
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