Kim Kiduk, Hong Gil-Sun, Kim Namkug
J Korean Soc Radiol. 2024 Sep;85(5):848-860. doi: 10.3348/jksr.2024.0066. Epub 2024 Sep 27.
The recent advent of large language models (LLMs), such as ChatGPT, has drawn attention to generative artificial intelligence (AI) in a number of fields. Generative AI can produce different types of data including text, images, and voice, depending on the training methods and datasets used. Additionally, recent advancements in multimodal techniques, which can simultaneously process multiple data types like text and images, have expanded the potential of using multimodal generative AI in the medical environment where various types of clinical and imaging information are used together. This review summarizes the concepts and types of LLMs, image generative AI, and multimodal AI, and it examines the status and future possibilities of generative AI in the field of radiology.
最近，诸如ChatGPT之类的大语言模型（LLMs）的出现，引起了多个领域对生成式人工智能（AI）的关注。根据所使用的训练方法和数据集，生成式AI可以生成包括文本、图像和语音在内的不同类型的数据。此外，多模态技术的最新进展，即可以同时处理文本和图像等多种数据类型，扩大了在医学环境中使用多模态生成式AI的潜力，在医学环境中，各种类型的临床和影像信息是一起使用的。本综述总结了大语言模型、图像生成式AI和多模态AI的概念及类型，并探讨了生成式AI在放射学领域的现状和未来可能性。
