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Digital Twins in Healthcare: Simulation, Data, and the Future of Personalized Medicine

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  • Lyuben Zyumbilski

    (University of National and World Economy, Sofia, Bulgaria)

Abstract

Digital twins-virtual representations of physical systems continuously updated with real-world data are emerging as a transformative technology in healthcare. By integrating physiological models, medical data, and real-time patient information, digital twins enable simulation, prediction, and optimization of individual health states and treatment outcomes. This paper explores the concept and architecture of digital twins in medicine, focusing on data integration, modeling techniques, and the role of artificial intelligence in maintaining accurate and adaptive simulations. Ethical and privacy challenges are also discussed, along with the potential of digital twin ecosystems for clinical research, preventive medicine, and personalized treatment planning. The study concludes that digital twins represent a paradigm shift from reactive to proactive healthcare, driven by data, computation, and intelligent modeling.

Suggested Citation

  • Lyuben Zyumbilski, 2025. "Digital Twins in Healthcare: Simulation, Data, and the Future of Personalized Medicine," Innovative Information Technologies for Economy Digitalization (IITED), University of National and World Economy, Sofia, Bulgaria, issue 1, pages 274-278, October.
    • Handle: RePEc:nwe:iitfed:y:2024:i:1:p:274-278
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    File URL: https://www.unwe.bg/doi/iited/2025/IITED.2025.35.pdf
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