用AI生成医学视频，助力疾病模拟与教学
Artificial Intelligence for Biomedical Video Generation
- 基于Sora类模型生成高质量生物医学视频
- 构建多源数据集支持模型训练与评估
- 适合医学教育、科研及AI医疗开发者使用
作为人工智能生成内容（AIGC）的重要分支，视频生成近年来取得显著进展。Sora类模型的出现标志着视频生成技术的重大突破，极大提升了合成视频的质量。在生物医学领域，该技术展现出巨大潜力，可用于医学概念阐释、疾病过程模拟及生物医学数据增强。本文系统梳理了视频生成模型的最新进展，探讨其在生物医学中的应用、挑战与未来机遇。我们整合了来自多个来源的全面数据集，以促进生物医学视频生成模型的研发与评估。鉴于该领域发展迅速，我们还建立了GitHub仓库（https://github.com/Lee728243228/Biomedical-Video-Generation），持续更新相关进展。
原文摘要 · Abstract (English)
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
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