Researchers at King's College London, The Alan Turing Institute, and the University of Cambridge in the U.K. and the University of Texas at Austin (UT Austin) say that digital twin technology can play a significant role in predictive and precision medicine and improving decision-making for aerospace systems.
However, they argue that the technical barriers to the adoption of digital twins must be reduced substantially for them to be achieved at scale.
King's College's Steven Niederer said, "We also need to further develop the mathematics of how we create digital twins from patient data, how we measure uncertainty in patient data, and how to account for uncertainty in the model in predictions. These are all things which need further investment."
However, UT Austin's Karen Willcox said, "Even with existing limitations, digital twins are providing valuable decision support in many different application areas."
From King's College London News Center
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