Could digital twins be the next revolution in healthcare?

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 im...

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Publicado en:European Journal of Public Health Vol. 35; no. 1; pp. 19 - 26
Autores principales: El-Warrak, Leonardo de Oliveira, Farias, Claudio Miceli de
Formato: review tables/charts Journal Article
Publicado: Oxford University Press / USA Feb2025
Acceso en línea:Ver este registro en EBSCOhost
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          El-Warrak, Leonardo de Oliveira
          Farias, Claudio Miceli de
        affil: COPPE—Graduate School and Research in Engineering, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
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        subj:
          Artificial Intelligence
          Individualized Medicine
          Digital Health
          Health Care Delivery Trends
          Health Care Industry
          Digital Technology
          Telehealth
          Patient Care
          Data Management
          Decision Making
          Privacy and Confidentiality
      ab: 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.
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