医疗图像中的生成AI和基础模型
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
概括
包括扩散模型和大型语言模型 (LLM) 在内的生成人工智能正在通过增强医疗图像处理和文本生成来彻底改变医疗保健. 基金会模型是开发先进AI用于医疗支持的关键.
科学领域:
- 人工智能的人工智能
- 医疗信息学 医疗信息学
- 计算机科学 计算机科学
背景情况:
- 生成型人工智能,包括扩散模型和大型语言模型 (LLM),已经在各个领域迅速扩展.
- 在大型数据集上训练的基础模型代表了AI开发的新范式,具有通用知识.
- 这些进展显著影响医疗图像处理和医疗保健中的AI开发.
研究的目的:
- 为图像生成AI和文本生成AI的LLM提供扩散模型的概述.
- 在医疗支持中引入它们的应用.
- 讨论基础模型,其构造和医疗应用.
主要方法:
- 扩散模型和大型语言模型 (LLM) 的概述.
- 基础模型建设的探索.
- 分析AI在医疗支持和图像处理中的应用.
主要成果:
- 生成型人工智能和基础模型正在改变医疗保健中的人工智能开发框架.
- 扩散模型和LLM在医学图像和文本生成任务中显示出重大潜力.
- 基础模型在医疗领域提供了多样化的应用.
结论:
- 生成性AI和基础模型正在从根本上改变医疗保健中的AI发展.
- 进一步开发基础模型和高性能AI用于医疗支持至关重要.
- 利用国家数据和计算资源是推动医疗人工智能的关键.
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