A Revolution of Personalized Healthcare: Enabling Human Digital Twin
  with Mobile AIGC
Jiayuan Chen Changyan Yi Hongyang Du Dusit Niyato Jiawen Kang Jun Cai Xuemin Shen
Mobile Artificial Intelligence-Generated Content (AIGC) technology refers to
the adoption of AI algorithms deployed at mobile edge networks to automate the
information creation process while fulfilling the requirements of end users.
Mobile AIGC has recently attracted phenomenal attentions and can be a key
enabling technology for an emerging application, called human digital twin
(HDT). HDT empowered by the mobile AIGC is expected to revolutionize the
personalized healthcare by generating rare disease data, modeling high-fidelity
digital twin, building versatile testbeds, and providing 24/7 customized
medical services. To promote the development of this new breed of paradigm, in
this article, we propose a system architecture of mobile AIGC-driven HDT and
highlight the corresponding design requirements and challenges. Moreover, we
illustrate two use cases, i.e., mobile AIGC-driven HDT in customized surgery
planning and personalized medication. In addition, we conduct an experimental
study to prove the effectiveness of the proposed mobile AIGC-driven HDT
solution, which shows a particular application in a virtual physical therapy
teaching platform. Finally, we conclude this article by briefly discussing
several open issues and future directions.