Digital Twins for Health A Scoping Review
by Katsoulakis et al
Definition & Character of digital twin:
A virtual representation of objects
Faithfully mirror the real-world system in real-time, analyze its behavior and provide predictive insights using advanced simulation, ML and reasoning.
Types of Digital Twin
Static twin: A digital replica of a physical system
Mirror (functional) twin: A static twin with dynamic behavior capabilities
Shadow (self-adaptive) twin: A functional twin with the capacity to acquire real-time data and update the model
Intelligent (extended/cognitive/physical avatars) twin: Self-adaptive twin with a degree of artificial intelligence that has autonomy with learning, reasoning, knowledge, and acting capabilities.
Different types of DTs for healthcare:
Provided a somewhat OK overview of different applications.
(Thoughts): LLM vs. ML models
ML models have limited functions. A prediction model can only do prediction. However, if we replace the inference part with an LLM, the final product will be moved into the realm of a digital twin.
Digital phenotype: patterns in human body and behavior. (Input to DT construction).
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