Year: 2026
Type: article
Abstract: Deepfake technology, driven by advancements in deep learning and large language models, has found widespread applications across various fields. In the context of physical health management and application, deepfake presents new possibilities for media production, athlete representation, training enhancement, and historical event recreation. This review explores the multifaceted applications of deepfake in the health industry with the help of various generative technologies like large language models, analyzing its potential to transform broadcasting, virtual athlete branding, and tactical simulation. While the technology offers numerous benefits, it also poses significant risks, such as the spread of misinformation, privacy violations, unfair competition, and ethical dilemmas. This paper addresses these challenges and discusses the regulatory measures needed to ensure the ethical deployment of deepfake technology in physical health. Additionally, it highlights emerging detection techniques and suggests proactive strategies for health organizations to mitigate deepfake‐related threats. The review concludes with an outlook on future innovations, emphasizing the importance of balancing technological advancement with legal and ethical considerations to safeguard the integrity of the health industry.
DOI: 10.1155/int/9983200
Authors: Tengfei Fan, Mohammad Mahdi Moghimi
Institutions: Qufu Normal University, Islamic Azad University, Yazd
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,700
Award: G3617549535
OpenAlex ID: W7127053140