Precision medicine envisages a changed paradigm for health care through better understanding of individual disease susceptibility and prognosis, enabling more personalized treatment. Enabling technologies such as the health digital twin are rapidly evolving, presenting important challenges and opportunities to be tackled within local contexts.
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The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field
npj Digital Medicine Open Access 26 August 2022
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References
Dilsizian, M. E. & Siegel, E. L. Machine meets biology: a primer on artificial intelligence in cardiology and cardiac imaging. Curr. Cardiol. Rep. 20, 139 (2018).
Vernon, S. T. et al. ST-segment-elevation myocardial infarction (STEMI) patients without standard modifiable cardiovascular risk factors-how common are they, and what are their outcomes? J. Am. Heart Assoc. 8, e013296 (2019).
Finkel, A., Wright, A., Pineda, S. & Williamson, R. Precision medicine. Australia’s Chief Scientist https://www.chiefscientist.gov.au/sites/default/files/Precision-medicine-final.pdf (2018).
Williamson, R. et al. The Future of Precision Medicine in Australia. Australian Council of Learned Academies https://acola.org/hs2-precision-medicine-australia/ (2018).
Hawgood, S., Hook-Barnard, I. G., O’Brien, T. C. & Yamamoto, K. R. Precision medicine: beyond the inflection point. Sci. Transl Med. 7, 300ps317 (2015).
Kamel Boulos, M. N. & Zhang, P. Digital twins: from personalised medicine to precision public health. J. Pers. Med. 11, 745 (2021).
Bruynseels, K., Santoni de Sio, F. & van den Hoven, J. Digital twins in health care: ethical implications of an emerging engineering paradigm. Front. Genet. 9, 31 (2018).
Martinez-Velazquez, R., Gamez, R. & Saddik, A. E. Cardio twin: a digital twin of the human heart running on the edge. 2019 IEEE International Symposium on Medical Measurements and Applications (MeMeA) https://doi.org/10.1109/MeMeA.2019.8802162 (2019).
Jones, G., Parr, J., Nithiarasu, P. & Pant, S. Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database. Biomech. Model. Mechanobiol. https://doi.org/10.1007/s10237-021-01497-7 (2021).
Hirschvogel, M., Jagschies, L., Maier, A., Wildhirt, S. M. & Gee, M. W. An in silico twin for epicardial augmentation of the failing heart. Int. J. Numer. Method. Biomed. Eng. 35, e3233 (2019).
Acknowledgements
The authors gratefully acknowledge Victoria Snelson of the University of Sydney Cardiovascular Initiative. G.C. is supported by an Ignite Award from the University of Sydney Cardiovascular Initiative.
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DigiTwins: https://www.digitwins.org/
Medical Digital Twin for Aneurysm Prevention and Treatment (MeDiTATe): https://meditate-project.eu/
Swedish Digital Twin Consortium: https://www.sdtc.se/
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Coorey, G., Figtree, G.A., Fletcher, D.F. et al. The health digital twin: advancing precision cardiovascular medicine. Nat Rev Cardiol 18, 803–804 (2021). https://doi.org/10.1038/s41569-021-00630-4
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DOI: https://doi.org/10.1038/s41569-021-00630-4
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