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Biases in end-to-end digital twins built from chained models
US & West ·
The work examines the statistical properties of a Monte Carlo scheme that forwards full predictive draws through a chain of separately fitted stage models. Two-stage analytical examples show persistent interval and coverage inflation and, with quadratic propagation, parameter-dependent mean bias; simulations of four- and eight-stage chains confirm pronounced distortions.
Why it matters
It warns that naively assembling a twin from stage models yields biased predictions and points to where correction is needed in end-to-end modelling.
Next-generation wireless networks are increasingly large-scale, heterogeneous, and dynamic, posing significant challenges to network modeling and control. Digital twins offer a promising solution, but existing approaches typically rely on static models and decouple twin construction from network…
Cardiac digital twins (CDTs) provide a computational platform for personalized cardiac modeling, but their predictive behavior depends strongly on the selected ionic model and the representation of transmural electrophysiological heterogeneity.
