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Cardiovascular Digital Twins: From Physics to Data
US & West ·
This review examines approaches to creating digital twins of the cardiovascular system: mechanistic models with physiological interpretability but high computational costs, and data-driven methods with better scalability but limited robustness. Hybrid approaches, including physics-informed and graph-based methods, are described, along with validation challenges and pathways to clinical deployment.
Why it matters
Important for understanding the applicability limits and prospects of hybrid modeling methods in medicine, relevant to the development of digital twins of complex biological systems.
Growing interest in in-space servicing, manufacturing, and assembly has renewed attention on reliable metal joining for modular construction and on-orbit repair. Robotic welding is promising, but reduced-gravity and low-pressure operation remains poorly characterised and flight-like tests are…
Digital twins (DTs) can generate dense synthetic fingerprints for localization via ray tracing, yet the sim-to-real domain gap limits their direct use, particularly in cell-free millimeter-wave (mmWave) deployments where distributed geometries and blockage-induced sparsity widen the mismatch.
Catheter obstruction is the commonest cause of shunt failure; freehand insertion at Keen's point leaves the tip free in cerebrospinal fluid in only one case in ten. We built a digital twin that reconstructs skull, scalp, ear and ventricles from preoperative CT by deterministic geometry, searches…