de Oliveira El-Warrak Leonardo, Miceli de Farias Claudio
COPPE-Graduate School and Research in Engineering, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
Eur J Public Health. 2025 Feb 1;35(1):19-25. doi: 10.1093/eurpub/ckae191.
A Digital Twin (DT) can be understood as a representation of a real asset, a virtual replica of a physical object, process, or even a system. They have been used in managing healthcare facilities, streamlining care processes, personalizing treatments, and enhancing patient recovery. The potential impact of this tool on our society and its well-being is quite significant. A quick review of the literature was carried out using the terms ('Digital Twins') and ('Digital Health'), and (Health Care) with a time interval of up to 5 years (2018-23). Using the PRISMA Method, the search was conducted in six academic databases: IEEE Xplore, Dimensions, Scopus, Web of Science, PubMed, and ACM. After applying the search strings and the exclusion criteria, a total of 13 publications were identified and listed to constitute and support the discussion of this article. The selected studies were categorized into 2 groups according to their application in healthcare: A group of clinical applications, subdivided into topics on personalized care and reproduction of biological structures and another group of operational applications, subdivided into topics such as optimization of operational processes, reproduction of physical structures, and development of devices and drugs. The use of DT in healthcare presents important challenges related to data integration, privacy, and interoperability. However, trends indicate exciting potential in personalizing treatment, prevention, remote monitoring, informed decision-making, and process management, which can result in significant improvements in quality and efficiency in healthcare.
数字孪生(DT)可以被理解为真实资产的一种表示形式,是物理对象、过程甚至系统的虚拟副本。它们已被用于管理医疗保健设施、简化护理流程、个性化治疗以及促进患者康复。这个工具对我们的社会及其福祉的潜在影响相当重大。使用术语“数字孪生”、“数字健康”和“医疗保健”进行了快速文献综述,时间跨度长达5年(2018 - 2023年)。使用PRISMA方法,在六个学术数据库中进行了搜索:IEEE Xplore、Dimensions、Scopus、科学网、PubMed和ACM。应用搜索词和排除标准后,共识别并列出了13篇出版物,以构成并支持本文的讨论。根据在医疗保健中的应用,所选研究分为两组:一组是临床应用,细分为个性化护理和生物结构再现等主题;另一组是运营应用,细分为运营流程优化、物理结构再现以及设备和药物开发等主题。DT在医疗保健中的应用带来了与数据集成、隐私和互操作性相关的重要挑战。然而,趋势表明在个性化治疗、预防、远程监测、明智决策和流程管理方面具有令人兴奋的潜力,这可以显著提高医疗保健的质量和效率。