Digital twins are advanced digital replicas of physical systems, processes, or entities that use real-time data, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to simulate, monitor, and predict the behavior of their real-world counterparts. In healthcare, digital twins can represent anything from a human organ, medical device, or hospital infrastructure to an entire patient, enabling precise simulations and personalized interventions.
The concept of digital twins traces back to the early 2000s, when Dr. Michael Grieves at the University of Michigan first introduced the idea in the context of product lifecycle management,...
