4 papers
Machine Learning Framework for Thrombosis Risk Prediction in Rotary Blood Pumps
Christopher Blum, Michael Neidlin
Thrombosis in rotary blood pumps arises from complex flow conditions that remain difficult to translate into reliable and interpretable risk predictions using existing computationa…
Bayesian Parameter Inference and Uncertainty-Informed Sensitivity Analysis in a 0D Cardiovascular Model for Intraoperative Hypotension
Jan-Niklas Thiel, Marko Zlicar, Ulrich Steinseifer +2
Computational cardiovascular models are promising tools for clinical decision support, particularly in complex conditions, such as intraoperative hypotension (IOH). IOH arises from…
Characterizing Intraventricular Flow Patterns via Modal Decomposition Techniques in Idealized Left Ventricle Models
Eneko Lazpita, Michael Neidlin, Jesus Garicano-Mena +1
Understanding the formation, propagation, and breakdown of the main vortex ring (VR) is essential for characterizing left ventricular (LV) hemodynamics, as its dynamics have been l…
Possible Contexts of Use for In Silico trials methodologies: a consensus-based review
Marco Viceconti, Luca Emili, Payman Afshari +15
The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diag…