A Revolution of Personalized Healthcare: Enabling Human Digital Twin with Mobile AIGC

计算机科学 医疗保健 移动计算 计算机网络 移动电话技术 计算机安全 互联网隐私 移动无线电 经济增长 经济
作者
Jiayuan Chen,Changyan Yi,Hongyang Du,Dusit Niyato,Jiawen Kang,Jun Cai,Xuemin Shen
出处
期刊:IEEE Network [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1 被引量:8
标识
DOI:10.1109/mnet.2024.3366560
摘要

Mobile artificial intelligence-generated content (AIGC) refers to the adoption of generative artificial intelligence (GAI) 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.

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