Imagine a hospital where a doctor is reading test results from two cancer patients. One is a 62-year-old woman, who sits in the exam room waiting to discuss her treatment options. The other is her virtual representation — a set of simulations and models that mimic the patient and the tumor. Together, the real-world patient, her virtual counterpart, and the flow of information between the two form a system called a digital twin.
Results from imaging or lab tests on the patient update the virtual representation, which feeds into simulations of how the patient’s body might respond to different potential therapies. Doctors could use such insights to minimize invasive testing on already weary and sick patients, and to develop personalized care plans that avoid unnecessary treatments — simultaneously making patients’ lives easier, optimizing the outcomes, and reducing health care costs. Over the past several years, advancements in digital twin technologies — which use modeling and simulation to create a virtual representation that mimics the structure, context, and behavior of its physical counterpart — means this scenario is coming closer to being realized. Going beyond traditional simulation and modeling, digital twins feature bidirectional feedback — think of it as a continuous back and forth chatter — between their virtual and...Read more...
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