Advancing Healthcare Systems with Generative AI-Driven Digital Twins

The healthcare sector is undergoing a digital transformation thanks to new technologies, with digital twinning and generative artificial intelligence (AI) leading the innovation. Digital twins, conceptualized originally as engineering or manufacturing tools, are increasingly finding their way to the healthcare sector, in response to the growing need for sophisticated virtual patient representations with scope for modeling several complex biological systems. Empowered by generative AI, digital twins, as they start to replace static models, open their gates into dynamic, predictive, prescriptive systems, enabling personalized healthcare delivery, disease modeling, surgical planning, and drug discovery. This paper reviews the combined potential of AI and digital twin technologies in the healthcare domain. It delivers a comprehensive view on the present possible applications, benefits, and opportunities of technology while putting in perspective the challenges regarding data privacy, ethical, computational, and design biases. By intertwining results from various studies and companies, the research thereby expounds into realizing the positive thrust capability of generative AI digital twins in influencing the transformation of healthcare delivery toward more stringent, predictive, preventive medicine. The paper identifies future research directions crucial to confronting current challenges and ensuring the responsible deployment of these technologies in healthcare systems across the globe.