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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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Generative AI and foundation models in medical image
Masahiro Oda1,2
1Data Science Research Division, Information Technology Center, Nagoya University, Furo-cho, Chikusa-ku, 464-8601, Nagoya, Japan. moda@mori.m.is.nagoya-u.ac.jp.
Radiological Physics and Technology
|October 6, 2025
Summary
Generative AI, including diffusion models and large language models (LLMs), is revolutionizing healthcare by enhancing medical image processing and text generation. Foundation models are key to developing advanced AI for medical support.
Area of Science:
- Artificial Intelligence
- Medical Informatics
- Computer Science
Background:
- Generative AI, including diffusion models and large language models (LLMs), has seen rapid expansion across diverse domains.
- Foundation models, trained on large datasets, represent a new paradigm in AI development with general-purpose knowledge.
- These advancements significantly impact medical image processing and AI development in healthcare.
Purpose of the Study:
- To provide an overview of diffusion models for image generation AI and LLMs for text generation AI.
- To introduce their applications in medical support.
- To discuss foundation models, their construction, and medical applications.
Main Methods:
- Overview of diffusion models and large language models (LLMs).
- Exploration of foundation model construction.
- Analysis of AI applications in medical support and image processing.
Main Results:
- Generative AI and foundation models are transforming AI development frameworks in healthcare.
- Diffusion models and LLMs show significant potential in medical image and text generation tasks.
- Foundation models offer versatile applications within the medical field.
Conclusions:
- Generative AI and foundation models are fundamentally changing AI development in healthcare.
- Further development of foundation models and high-performance AI for medical support is crucial.
- Leveraging national data and computational resources is key to advancing medical AI.
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