Digital Twins in Healthcare: State of the Art, Bibliometric Analysis and Future Perspectives

Digital Twins (DTs) are reshaping healthcare by providing dynamic, digital counterparts of physical systems, enabling real-time interaction, simulation, and analysis. These systems leverage advanced modeling and real-world data integration to optimize medical training, planning, and patient-specific care. This paper explores the evolution of DTs in healthcare, presenting a bibliometric analysis of trends and outlying future directions. The state-of-the-art section highlights technological advances in DTs, with a particular focus on simulating complex physiological behaviors. These advancements align with the growing demand for precision in surgical training and planning. The bibliometric analysis reveals an exponential increase in research interest, driven by advancements in Artificial Intelligence (AI), immersive technologies, and real-time data processing. Cross-disciplinary efforts, combining fields such as computer science, biomechanics, and medical engineering, are highlighted as key enablers, expanding the applicability of DTs. Future perspectives emphasize the transformative potential of DTs in remote surgical procedures, augmented diagnostics, and personalized medicine. The integration of Augmented Reality (AR) and Virtual Reality (VR) enhances the user experience by providing immersive, interactive environments. Additionally, the inclusion of haptic feedback and sensor-based tracking further augments realism, improving usability and adoption. Through the case study of the Rome Technopole project “Phygital Twin Technologies for Innovative Surgical Training & Planning”, this paper showcases how DTs are already impacting healthcare, from training simulators to patient specific planning tools. Furthermore, the discussion points to new frontiers, such as integrating predictive analytics for proactive healthcare interventions.