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Concepts and applications of digital twins in healthcare and medicine

The Combine·17h ago·1 view
Authors: Kang Zhang, Hong-Yu Zhou, Daniel Tomas Baptista‐Hon, Yuanxu Gao, Xiaohong Liu, Eric Karl Oermann, Sheng Hua Xu, Shengwei Jin, Jian Zhang, Zhuo Sun, Yun Yin, Ronald M. Razmi, Alexandre Loupy, Stephan Beck, Jia Qu, Joseph WuField: PatternsYear: 2024DOI: 10.1016/j.patter.2024.101028 148 citations

The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.

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