article · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
Digital twins are virtual replicas of physical entities that update with real-time data to predict the behaviour of their physical counterparts. In healthcare, this technology supports a clearer understanding of disease occurrence, facilitating more accurate diagnoses and targeted treatments. Implementing digital twins relies on the integration of emerging technologies, such as big data, cloud computing, virtual reality, and the internet of things. Despite difficulties in defining digital twins within medical contexts, they offer transformative opportunities for precision healthcare and personalised medicine. Specific application areas include healthcare 4.0, cardiac analysis, patient monitoring, management, surgical procedures, and considerations surrounding data privacy and socio-ethical issues. Software tools, simulations, and future technological trends provide the operational basis for these diverse healthcare deployments.
Digital twins offer a way to simulate human biology and hospital operations using live data. By combining connected devices with advanced computing, healthcare providers can better understand how illnesses develop. This enables personalised medical interventions, improves clinical decision-making, and supports safer surgical planning, ultimately leading to more precise and effective healthcare delivery for patients.
The work highlights applications for medical technology developers, clinicians, and hospital administrators in areas like cardiac analysis, remote monitoring, and surgical simulation. Because the review focuses on software tools, simulation models, and conceptual frameworks alongside technical and socio-ethical challenges, the overall domain remains primarily in an exploratory and early-stage research phase rather than offering immediate commercial deployment.
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Abstract The healthcare industry has witnessed significant interest in applying DTs (DTs), due to technological advancements. DTs are virtual replicas of physical entities that adapt to real‐time data, enabling predictions of their physical counterparts. DT technology enhances understanding of disease occurrence, enabling more accurate diagnoses and treatments. Integrating emerging technologies like big data, cloud computing, Virtual Reality (VR), and internet‐of‐things (IoT) provides a solid foundation for DT implementation in healthcare. However, defining DTs within the healthcare context still has become increasingly challenging. Therefore, exploring the potential of DTs in healthcare contributes to research, emphasizing their transformative impact on personalized medicine and precision healthcare. In this study, we present diverse healthcare applications of DTs, including healthcare 4.0, cardiac analysis, monitoring and management, data privacy, socio‐ethical, and surgical. Moreover, this paper discusses the software and simulations of DTs that can be used in these applications of healthcare, as well as, the future trends of DTs in healthcare. This article is categorized under: Application Areas > Health Care Technologies > Computational Intelligence
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DOI: 10.1002/widm.1559
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