Lei Shi

Measurement-Dependent Parameter Recoverability in Neural Cardiovascular LPN Inference

The paper evaluates parameter recoverability in cardiovascular LPN inference using a probabilistic neural framework, showing that accurate hemodynamic prediction does not guarantee correct parameter recovery.

Personalized biventricular mechanics and sensitivity to model morphology

The paper develops a patient-specific cardiac mechanics model using clinical data and evaluates its performance against simplified models, finding that truncation significantly affects results.

A finite element model of pregnancy derived from maternal sonography: effect of uterine and cervical structural properties on cervical mechanical loading

This study uses finite element modeling to analyze how uterine and cervical structural properties affect cervical mechanical loading during pregnancy, identifying key parameters influencing preterm birth risk.

A Method for Image-Based Modeling of Uterine Passive Mechanics During Late Pregnancy

The paper develops an image-based modeling pipeline to study uterine passive mechanics during late pregnancy, achieving computational savings and accurate strain predictions.

Effects of Left Atrial Wall Thickness on Myocardial Mechanics and Blood Dynamics using Multiscale Modeling

This study uses multiscale modeling to show that left atrial wall thickness significantly affects myocardial stresses and oscillatory shear, more than other factors like cavity volume or displacement.