article · IEEE Internet of Things Magazine
Generative Artificial Intelligence (GAI) and the Internet of Medical Things (IoMT) are rapidly transforming the healthcare landscape. Their convergence, termed GAIoMT, offers a powerful paradigm that combines GAI’s ability to generate synthetic data, support predictive analytics, and enable autonomous decision-making with IoMT’s real-time sensing and connectivity capabilities. This paper introduces and formalizes the concept of GAIoMT, presenting a layered architectural framework that illustrates how generative models can be integrated across medical devices, data infrastructures, and clinical workflows. A thematically structured review of the current literature is provided along with performance and complexity analysis across representative GAIoMT methods. A practical use case scenario is included to demonstrate real-world applicability, particularly in chronic disease management. Finally, we identify key challenges and outline future research directions for building robust, explainable, and inclusive GAIoMT systems.
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DOI: 10.1109/miot.2025.3578949
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