Text-to-video generative artificial intelligence: sora in neurosurgery

被引:11
作者
Mohamed, Ali A. [1 ,2 ]
Lucke-Wold, Brandon [3 ]
机构
[1] Florida Atlantic Univ, Charles E Schmidt Coll Med, Boca Raton, FL 33431 USA
[2] Florida Atlantic Univ, Coll Engn & Comp Sci, Boca Raton, FL 33431 USA
[3] Univ Florida, Lillian S Wells Dept Neurosurg, Gainesville, FL USA
关键词
ChatGPT; Computer vision; Large language models; Patient education; Training; Virtual reality; DISKECTOMY;
D O I
10.1007/s10143-024-02514-w
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Artificial intelligence (AI) has increased in popularity in neurosurgery, with recent interest in generative AI algorithms such as the Large Language Model (LLM) ChatGPT. Sora, an innovation in generative AI, leverages natural language processing, deep learning, and computer vision to generate impressive videos from text prompts. This new tool has many potential applications in neurosurgery. These include patient education, public health, surgical training and planning, and research dissemination. However, there are considerable limitations to the current model such as physically implausible motion generation, spontaneous generation of subjects, unnatural object morphing, inaccurate physical interactions, and abnormal behavior presentation when many subjects are generated. Other typical concerns are with respect to patient privacy, bias, and ethics. Further, appropriate investigation is required to determine how effective generative videos are compared to their non-generated counterparts, irrespective of any limitations. Despite these challenges, Sora and other iterations of its text-to-video generative application may have many benefits to the neurosurgical community.
引用
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页数:4
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