A Review: Integration of AI, XR and Digital Twin Technologies in Biomedical Engineering

Vollständiger Abstract

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Biomedical Engineering (BME) sits at the intersection of engineering, biology, and clinical medicine, and its tools and methods are increasingly reshaped by two converging digital forces: Artificial Intelligence (AI) and Extended Reality (XR). This review synthesizes the literature to examine how AI, spanning machine learning, deep learning, and generative models, is being applied across biomedical domains, including precision medicine, diagnostic imaging, oncology, robotic surgery, electronic health record (EHR) analytics, and clinical workflow automation. It further examines XR technologies, virtual reality (VR), augmented reality (AR), and mixed reality (MR), and their expanding role in medical education, surgical simulation, digital twin modeling, and immersive training environments historically pioneered by programs such as NASA's astronaut training initiative. The review then considers the convergence of AI and XR into intelligent, immersive biomedical systems, drawing on adjacent computational advances in accelerated computing, regenerative medicine, organoid engineering, and novel biomedical data storage. Finally, it addresses cross-cutting challenges: ethical implementation, health equity, regulatory oversight, cybersecurity, workforce disruption, and intellectual property. By consolidating findings across foundational BME literature, contemporary AI research, and emerging XR standards, this review aims to provide biomedical engineers, clinicians, and policymakers with a structured understanding of where these technologies currently stand and where continued research is most needed.