Digital twins for the era of personalized surgery.
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Abstract
Digital twins can aid surgeons in training and in performing interventions with greater awareness and precision. The range and variety of digital twins in surgery are described, and their use across perioperative care is discussed. While largely experimental, they are beginning to show promise for the enhancement of personalized, adaptive, and data-driven surgical care. Issues relevant to the greater adoption and deployment of digital twins are all considered.
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Acknowledgements: Credits to Liu et al.47 for Figure 3. Their article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. M.A.S. acknowledges support from Qatar Research, Development and Innovation Fund (NPRP13S-0119-200108). A.F.F. acknowledges support from the Royal Academy of Engineering under the RAEng Chair in Emerging Technologies (INSILEX CiET1919/19), ERC Advanced Grant – UKRI Frontier Research Guarantee (INSILICO EP/Y030494/1). The research was carried out at the National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre (BRC) (NIHR203308). J.Q. acknowledges support from Qatar University HIG 23/24-127.
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2398-6352
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