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Photographic and Video Deepfakes Have Arrived: How Machine Learning May Influence Plastic Surgery
Dustin T Crystal1, Nicholas G Cuccolo1, Ahmed M S Ibrahim1
1From the Division of Plastic Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School; and the Division of Plastic Surgery, Department of Surgery, Stanford University Medical Center.
Abstract:
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.

