Swinburne University of Technology, Australia.
Villanova University, USA.
Stud Health Technol Inform. 2024 Jan 25;310:229-233. doi: 10.3233/SHTI230961.
The use of Digital Twins (DTs) or the digital replicas of physical entities has provided benefits to several industry sectors, most notably manufacturing. To date, the application of DTs in the healthcare sector has been minimal, however. But, as pressure increases for more precise and personalized treatments, it behooves us to investigate the potential for DTs in the healthcare context. As a proof-of-concept demonstration prior to working with real patients, we attempt in this paper, to explore the potential for creating and using DTs. We do this in a synthetic environment at this stage, making use of data that is all computer-generated. DTs of synthetic present patients are created making use of data of synthetic past patients. In the real world, the clinical objective for creating such DTs of real patients would be to enable enhanced real-time clinical decision support to enable more precise and personalized care. The objective of the numerical experiment reported in this paper, is to envisage the possibilities and challenges of such an approach. We attempt to better understand the strengths and weaknesses of applying DTs in the healthcare context to support more precise and personalized treatments.
数字孪生体（DTs）或物理实体的数字复制品的使用为许多行业部门带来了好处，其中制造业最为显著。迄今为止，DT 在医疗保健领域的应用还很少。但是，随着对更精确和个性化治疗的需求压力不断增加，我们有必要研究 DTs 在医疗保健环境中的潜力。作为在与真实患者合作之前的概念验证演示，我们在本文中尝试探索创建和使用 DTs 的潜力。在现阶段，我们在合成环境中进行此项工作，利用全部由计算机生成的数据。利用合成过去患者的数据，创建了合成现有患者的 DTs。在现实世界中，创建此类真实患者 DTs 的临床目标是为了能够增强实时临床决策支持，以实现更精确和个性化的护理。本文报告的数值实验的目的是设想这种方法的可能性和挑战。我们试图更好地了解在医疗保健环境中应用 DTs 来支持更精确和个性化治疗的优势和劣势。
