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Found 7 papers, 0 papers with code
Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression
For instance, Transcranial Doppler ultrasound (TCD) is a noninvasive clinical tool that is commonly used in the clinical settings to measure blood velocity waveform at several locations on brain's vasculature.
Physics-informed UNets for Discovering Hidden Elasticity in Heterogeneous Materials
We show superior performance, both in terms of accuracy and computational cost, by El-UNet compared to fully-connected physics-informed neural networks in estimating unknown parameters and stress distributions for isotropic linear elasticity.
Associating Frailty and Dynamic Dysregulation between Motor and Cardiac Autonomic Systems
The goal of the present study was to determine the effect of frailty on the interconnection between motor and cardiac systems during a localized upper-extremity function (UEF) test.
Hyperacute pathophysiology of traumatic and vascular brain injury captured by ultrasound, photoacoustic, and magnetic resonance imaging
Cerebrovascular dynamics and pathomechanisms that evolve in the minutes and hours following traumatic vascular injury in the brain remain largely unknown.
Cerebrovascular morphology in aging and disease -- imaging biomarkers for ischemic stroke and Alzheimers disease
Conclusion: Altered vessel geometry in AIS patients shows that there is pathological morphology coupled with stroke.
Physics-informed neural networks for improving cerebral hemodynamics predictions
Determining brain hemodynamics plays a critical role in the diagnosis and treatment of various cerebrovascular diseases.
Low-rank representation of head impact kinematics: A data-driven emulator
In characterizing our existing data set of 537 head impacts, consisting of 6 degrees of freedom measurements, we found that only a few modes, e. g. 15 in the case of angular velocity, is sufficient for accurate reconstruction of the entire data set.
