As a prominent subfield of Artificial Intelligence Generated Content (AIGC), video generation has achieved notable advancements in recent years. The introduction of Sora-alike models represents a pivotal breakthrough in video generation technologies, significantly enhancing the quality of synthesized videos. Particularly in the realm of biomedicine, video generation technology has shown immense potential such as medical concept explanation, disease simulation, and biomedical data augmentation. In this article, we thoroughly examine the latest developments in video generation models and explore their applications, challenges, and future opportunities in the biomedical sector. We have conducted an extensive review and compiled a comprehensive list of datasets from various sources to facilitate the development and evaluation of video generative models in biomedicine. Given the rapid progress in this field, we have also created a github repository to regularly update the advances of biomedical video generation at: https://github.com/Lee728243228/Biomedical-Video-Generation

该研究解决了生物医学领域中视频生成技术的应用和挑战问题，重点介绍了最新的视频生成模型及其潜力。本文的关键见解在于通过全面的文献回顾和数据集汇编，推动视频生成模型在医疗说明、疾病模拟等方面的开发，预计将显著改善生物医学研究的效率和效果。

生物医学视频生成的人工智能