AI-enabled Digital Twins in Healthcare

This Research Topic has been initiated by the board members of the Digital Twins for Health Society (About DT4HS), a mission-driven society advancing healthcare and medicine through excellence in science, education, outreach, and community engagement in human digital twins.Digital twins (DTs), now prevalent across many fields, are seeing a surge of interest within healthcare. The vision of digital twins for health (DT4H) offers immense potential to revolutionize every aspect of the healthcare system, including its management, the delivery of care, and the maintenance of well-being. This progress is fueled by the growth of big data and continuous advancements in artificial intelligence (AI), machine learning, and high-performance computing, which provide the necessary expertise, theory, algorithms, and infrastructure to accelerate digital twin development. However, while digital twin research and development are underway in other sectors, DT4H is still in its early stages.GoalRecent advances in AI, machine learning, multiscale modeling, and high-performance computing are driving the rapid development of digital twins in healthcare. The goal of this Research Topic is to present pioneering research and development in the realm of DT technology, fostering an international synergy among all stakeholders. We envision the ongoing development of these DT technologies would lead to enhanced healthcare and improved quality of life for millions of people worldwide.Scope and Information for authorsIn this Research Topic, we welcome original contributions from the scientific community in the format of research articles, perspectives, and reviews. Potential topics include, but are not limited to:• Multimodal real-world data integration, curation, standard, and management• Multi-omics data and biomarker discovery in healthcare• Mathematical, statistical, and mechanistic modeling of organs and systems• Physics-informed machine learning• Modeling and simulations of time-series data•Natural language processing of electronic health records and clinical notes• Digital twin application in clinical trials• AI-assisted clinical decision support• Pharmacokinetics-Pharmacodynamics modeling of drug dynamics Topic editors: Jun Deng, Qi Wang Source: https://www.frontiersin.org/research-topics/74427/ai-enabled-digital-twins-in-healthcare