Huang Yu, Dai Hao, Xu Jie, Wei Ruoqi, Sun Leyang, Guo Yi, Guo Jingchuan, Bian Jiang
Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA.
Department of Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, FL, USA.
Res Sq. 2024 Aug 7:rs.3.rs-4612942. doi: 10.21203/rs.3.rs-4612942/v1.
An increasing amount of research is incorporating the concept of Digital twin (DT) in biomedical and health care applications. This scoping review aims to summarize existing research and identify gaps in the development and use of DTs in the health care domain. The focus of this study lies on summarizing: the different types of DTs, the techniques employed in DT development, the DT applications in health care, and the data resources used for creating DTs. We identified fifty studies, which mainly focused on creating organ- (n=15) and patient-specific twins (n=30). The research predominantly centers on cardiology, endocrinology, orthopedics, and infectious diseases. Only a few studies used real-world datasets for developing their DTs. However, there remain unresolved questions and promising directions that require further exploration. This review provides valuable reference material and insights for researchers on DTs in health care and highlights gaps and unmet needs in this field.
越来越多的研究将数字孪生（DT）概念纳入生物医学和医疗保健应用中。本综述旨在总结现有研究，并找出医疗保健领域数字孪生开发和使用方面的差距。本研究的重点在于总结：不同类型的数字孪生、数字孪生开发中采用的技术、数字孪生在医疗保健中的应用以及用于创建数字孪生的数据资源。我们确定了50项研究，这些研究主要集中在创建器官特异性（n = 15）和患者特异性孪生（n = 30）。研究主要集中在心脏病学、内分泌学、骨科和传染病领域。只有少数研究使用真实世界数据集来开发其数字孪生。然而，仍有一些未解决的问题和有前景的方向需要进一步探索。本综述为医疗保健领域数字孪生的研究人员提供了有价值的参考材料和见解，并突出了该领域的差距和未满足的需求。
