A new technological paradigm is emerging from the powerful symbiosis of three cornerstone technologies: eXtended Reality (XR), Digital Twins, and Artificial Intelligence (AI). In this new ecosystem, XR acts as the immersive portal for human interaction, Digital Twins serve as the dynamic, high-fidelity virtual counterparts to real-world objects and systems, and AI functions as the cognitive engine, processing vast amounts of data to derive insights, predict future states, and automate complex decisions. This integration moves us beyond siloed innovations by creating a feedback loop: human interactions in XR with the AI-enhanced Digital Twin generate new data that continuously refines the system, leading to a new era of intelligent and adaptive systems. In medicine, surgeons can now rehearse complex procedures on an AI-enhanced digital twin of a patient's organ within a realistic XR simulation.

The primary goal of this Research Topic is to catalyze and consolidate research at the intersection of XR, Digital Twins, and AI. We aim to move beyond theoretical discussions to showcase high-impact studies that present tangible advancements and rigorous evaluations. A central objective is to illuminate the measurable impact of these converged systems—quantifying improvements in surgical precision and training efficacy. To achieve this, we specifically seek contributions that introduce and validate novel architectures for seamless integration, address critical technical challenges such as real-time data fusion and scalability, and explore new paradigms for human-computer interaction within these intelligent, immersive environments. Ultimately, this collection will serve as a definitive, forward-looking resource that bridges the gap between foundational research and practical application. It will provide a clear roadmap for researchers, engineers, and industry leaders dedicated to developing the next generation of intelligent systems for medicine.

We invite the submission of original research articles, comprehensive reviews, and insightful case studies on the convergence of XR, Digital Twins, and AI. Submissions should be supported by clear evaluation metrics, with a strong preference for those measuring tangible medical outcomes such as improved surgical accuracy, reduced procedural errors, enhanced rehabilitation adherence, and increased training knowledge retention.

The scope of interest includes, but is not limited to, the following topics:

- Foundational Frameworks: Novel architectures and theoretical models for integrating XR, AI, and Digital Twins.

- Human-Computer Interaction (HCI): New interaction paradigms and multimodal interfaces for intuitive manipulation of AI-enhanced digital twins in XR.

- Predictive Analytics and Visualization: Combining AI-powered predictive models with immersive XR visualization for advanced diagnostics, operational planning, and decision-making.

- Applications in Medicine: Case studies and research on surgical training and planning, medical education, remote robotic procedures, patient-specific treatment simulation, and rehabilitation. We especially encourage submissions presenting clinical trials, pilot studies, and translational research that demonstrate tangible outcomes in real-world medical practice.

- Ethical and Governance Frameworks: Studies on data privacy, security, algorithmic bias, and human factors in deploying these integrated systems. Topics include patient consent, transparency of AI recommendations, liability frameworks, and data governance in clinical XR settings.

- While the primary focus is medicine, we also welcome high-quality submissions on industrial applications, such as smart manufacturing, remote assistance, quality control, and supply chain optimization.

Are you interested in contributing a manuscript to this Research Topic?

The Convergence of eXtended Reality (XR), Digital Twins, and Artificial Intelligence (AI) in Medicine