Health System Innovation Enabled by Artificial Intelligence, Digital Health, and Advanced Materials

The convergence of artificial intelligence, digital twin technology, and advanced materials science is fundamentally reshaping the landscape of biomedical engineering and health system design. From computationally guided development of bone repair scaffolds to real-time digital modeling of tissue regeneration processes and clinical decision workflows, these cross-disciplinary innovations are opening transformative pathways toward precision medicine and intelligent healthcare management. Despite considerable progress, substantial gaps persist between laboratory-stage material innovations and their real-world clinical translation—particularly in coherently integrating intelligent design methods with fabrication strategies, health communication frameworks, and large-scale emergency response systems. The growing complexity of modern healthcare further demands that bioengineering solutions be validated not only at the material level, but also across system-wide health governance and public health contexts.This Research Topic aims to unite cutting-edge contributions that bridge bioengineering and computational sciences to advance health system innovation across multiple dimensions. It seeks to highlight how AI-driven methodologies - including machine learning, Bayesian networks, digital platform analytics, and intelligent monitoring system development - can be synergistically applied alongside advanced biomaterial design and digital twin modeling to enhance diagnostic precision, therapeutic efficacy, and overall health system performance. Central questions guiding this collection include: How can digital technologies be co-developed with advanced materials to accelerate translational research pipelines? What computational frameworks most effectively support evidence-based clinical decision-making and public health emergency response? And how can methodological rigor be maintained as bioengineering tools are deployed across diverse health governance and communication settings?This Research Topic is focused on work grounded in clearly defined bioengineering or computational methodologies. We welcome articles exploring, but not limited to, the following themes:o Regenerative biomaterials and smart responsive materials for bone repair and tissue engineeringo 3D printing and digital manufacturing for patient-specific implants and therapeutic constructso Digital twin modeling for tissue repair simulation and health system optimizationo AI and machine learning in biomaterial design, structure–property prediction, and preclinical validationo Translational frameworks linking intelligent material design to preclinical and clinical applicationo Identification, quality assessment, and governance of digital health informationo Behavior prediction and intelligent monitoring for public health and emergency managemento Bayesian networks and digital platform analytics for health communication and policy evaluationIn addition to original research, we encourage the submission of reviews, perspectives, methodological advances, and system modeling studies that demonstrate mechanistic insight, innovation, and application validation, with the shared aim of accelerating the translational journey from materials intelligence to meaningful health system impact. Topic editors: Tianze Sun, Yang Zhang Source: https://www.frontiersin.org/research-topics/81419/health-system-innovation-enabled-by-artificial-intelligence-digital-health-and-advanced-materials