Recent progress in machine learning (ML), together with advanced computational power,
have provided new research opportunities in cardiovascular modeling. While classifying …

Near-wall blood flow and wall shear stress (WSS) regulate major forms of cardiovascular
disease, yet they are challenging to quantify with high fidelity. Patient-specific computational …

Vascular calcification is the abnormal deposition of calcium phosphate complexes in blood
vessels, which is regarded as the pathological basis of multiple cardiovascular diseases …

Image-based patient-specific modelling of hemodynamics are gaining increased popularity
as a diagnosis and outcome prediction solution for a variety of cardiovascular diseases …

Hemodynamic prediction of carotid artery stenosis (CAS) is of great clinical significance in
the diagnosis, prevention, and treatment prognosis of ischemic strokes. While computational …

In this work the development of a machine learning-based Reduced Order Model (ROM) for
the investigation of hemodynamics in a patient-specific configuration of Coronary Artery …

Computational fluid dynamics (CFD) is a valuable tool for personalised, non-invasive
evaluation of hemodynamics in arteries, but its complexity and time-consuming nature …

Computational fluid dynamics (CFD) is a valuable asset for patient-specific cardiovascular-
disease diagnosis and prognosis, but its high computational demands hamper its adoption …

In this work, a non-intrusive data-driven ROM based on a POD–ANN approach is developed
for fast and reliable numerical simulation of blood flow patterns occurring in a patient …

The computational modelling of blood flow is known to provide vital hemodynamic
parameters for diagnosis and treatment-support for patients with valvular heart disease …