Photographic and Video Deepfakes Have Arrived: How Machine Learning May Influence Plastic Surgery
Photographic and Video Deepfakes Have Arrived: How Machine Learning May Influence Plastic Surgery
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DOI：
10.1097/prs.0000000000006697
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发表时间：
2020-04-01
影响因子：
3.6
通讯作者：
Lin, Samuel J.
中科院分区：
文献类型：
--
作者：
Crystal, Dustin T.;Cuccolo, Nicholas G.;Lin, Samuel J.
计算机科学和摄影技术的进步不仅无处不在，而且也在数量上影响着医学实践。软件和硬件技术的最新进展已经转化为高级人工神经网络的设计：计算机框架可以被认为是模仿人脑的算法。在实践中，这些网络具有计算功能，包括自主生成新颖的图像和视频，通常被称为“深度伪造”。“导致deepfakes的技术进步很容易适用于整形手术的各个方面，对患者，提供者和未来的研究都有好处和伤害。作为一个专业，整形外科应该认识到这些概念，适当地讨论它们，并采取措施防止恶意使用。本文的目的是突出这些新兴技术，并讨论它们与整形外科的潜在相关性。
Advances in computer science and photography not only are pervasive but are also quantifiably influencing the practice of medicine. Recent progress in both software and hardware technology has translated into the design of advanced artificial neural networks: computer frameworks that can be thought of as algorithms modeled on the human brain. In practice, these networks have computational functions, including the autonomous generation of novel images and videos, frequently referred to as "deepfakes." The technological advances that have resulted in deepfakes are readily applicable to facets of plastic surgery, posing both benefits and harms to patients, providers, and future research. As a specialty, plastic surgery should recognize these concepts, appropriately discuss them, and take steps to prevent nefarious uses. The aim of this article is to highlight these emerging technologies and discuss their potential relevance to plastic surgery.