Revolutionizing Patient Care with Medical IoT and Generative AI

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.