物联网医疗中生成式AI驱动的人类数字孪生：一项全面综述
Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Survey
AI总结：
本综述探讨了生成式人工智能（GAI）驱动的人类数字孪生（HDT）在物联网医疗中的实现，提出了总体框架并详细分析了数据获取、通信、建模等关键技术，展示了其在个性化监测、诊断、处方及康复等应用中的潜力。
摘要：
物联网（IoT）能够显著提升人类生活质量，特别是在医疗保健领域，这引起了人们对IoT医疗服务的广泛关注。同时，人类数字孪生（HDT）被提出作为一种创新范式，能够全面表征个体人体在数字世界中的复制，并实时反映其物理状态。自然而然地，HDT被设想为通过作为多功能且生动的人类数字测试平台，模拟结果并指导实际治疗，从而在医疗监护应用之外赋能IoT医疗。然而，成功建立HDT需要高保真虚拟建模和强大的信息交互，但可能面临数据稀缺、有偏和含噪的问题。幸运的是，一项近期流行的名为生成式人工智能（GAI）的技术可能是一个有前景的解决方案，因为它能够利用先进的AI算法自动创建、操作和修改有价值且多样化的数据。本综述特别关注GAI驱动的HDT在IoT医疗中的实现。我们首先介绍IoT医疗的背景以及GAI驱动的HDT的潜力。然后，我们深入探讨其基础技术，并提出GAI驱动的HDT的总体框架。此后，我们详细探索GAI驱动的HDT的实现，包括GAI支持的数据获取、通信、数据管理、数字建模和数据分析。此外，我们讨论了可被GAI驱动的HDT颠覆的典型IoT医疗应用，即个性化健康监测与诊断、个性化处方和个性化康复。最后，我们通过强调一些未来的研究方向来总结本综述。
英文摘要：
The Internet of things (IoT) can significantly enhance the quality of human life, specifically in healthcare, attracting extensive attentions to IoT-healthcare services. Meanwhile, the human digital twin (HDT) is proposed as an innovative paradigm that can comprehensively characterize the replication of the individual human body in the digital world and reflect its physical status in real time. Naturally, HDT is envisioned to empower IoT-healthcare beyond the application of healthcare monitoring by acting as a versatile and vivid human digital testbed, simulating the outcomes and guiding the practical treatments. However, successfully establishing HDT requires high-fidelity virtual modeling and strong information interactions but possibly with scarce, biased and noisy data. Fortunately, a recent popular technology called generative artificial intelligence (GAI) may be a promising solution because it can leverage advanced AI algorithms to automatically create, manipulate, and modify valuable while diverse data. This survey particularly focuses on the implementation of GAI-driven HDT in IoT-healthcare. We start by introducing the background of IoT-healthcare and the potential of GAI-driven HDT. Then, we delve into the fundamental techniques and present the overall framework of GAI-driven HDT. After that, we explore the realization of GAI-driven HDT in detail, including GAI-enabled data acquisition, communication, data management, digital modeling, and data analysis. Besides, we discuss typical IoT-healthcare applications that can be revolutionized by GAI-driven HDT, namely personalized health monitoring and diagnosis, personalized prescription, and personalized rehabilitation. Finally, we conclude this survey by highlighting some future research directions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
