Publications associées à Cardiac output estimated from an uncalibrated radial blood pressure waveform: validation in an in-silico-generated population

Publications associées (38)

OPTIMAL TRANSPORT-INSPIRED DEEP LEARNING FRAMEWORK FOR SLOW-DECAYING KOLMOGOROV \bfitn-WIDTH PROBLEMS: EXPLOITING SINKHORN LOSS AND WASSERSTEIN KERNEL

Reduced-order models (ROMs) are widely used in scientific computing to tackle high-dimensional systems. However, traditional ROM methods may only partially capture the intrinsic geometric characteristics of the data. These characteristics encompass the und ...

2025

Left atrial wall shear stress correlates with fibrosis in patients with atrial fibrillation

Nikolaos Stergiopoulos, Georgios Rovas

Left atrial wall fibrosis has an important role in atrial fibrillation (AF) because of the abnormal electrophysiological properties of the fibrotic areas. However, the mechanisms behind the development of left atrial fibrosis are not well understood. Here, ...

Springer Science and Business Media LLC2025

Gradient Approximation of Approximate Multipliers for High-Accuracy Deep Neural Network Retraining

Giovanni De Micheli, Chang Meng

Approximate multipliers (AppMults) are widely employed in deep neural network (DNN) accelerators to reduce the area, delay, and power consumption. However, the inaccuracies of AppMults degrade DNN accuracy, necessitating a retraining process to recover acc ...

Institute of Electrical and Electronics Engineers2025

Implementation of an epicardial implantable MEMS sensor for continuous and real-time postoperative assessment of left ventricular activity in adult minipigs over a short- and long-term period

Silvestro Micera

The sensing of left ventricular (LV) activity is fundamental in the diagnosis and monitoring of cardiovascular health in high-risk patients after cardiac surgery to achieve better short- and long-term outcome. Conventional approaches rely on noninvasive me ...

Aip Publishing2024

Novel theory and potential applications of central diastolic pressure decay time constant

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

2024

The role of computational methods in cardiovascular medicine: a narrative review

Alfio Quarteroni, Luca Dede', Christian Vergara, Stefano Pagani

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Ame Publishing Company2024

Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature

Danick Briand, Silvia Demuru, Jaemin Kim, Brince Paul Kunnel

Sweat secreted by the human eccrine sweat glands can provide valuable biomarker information during exercise. Real-time non-invasive biomarker recordings are therefore useful for evaluating the physiological conditions of an athlete such as their hydration ...

2023

A comprehensive mathematical model for cardiac perfusion

Alfio Quarteroni, Francesco Regazzoni, Christian Vergara

The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, v ...

Nature Portfolio2023

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Alfio Quarteroni, Luca Dede', Francesco Regazzoni

Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-b ...

Nature Portfolio2024

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

Apparatus for non-invasively computing cardio-vasculature parameters using morphology of uncalibrated pressure wave signal

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas

Systems and apparatus are provided for using a non-invasively monitored uncalibrated pressure signal from a patient to compute cardiac output and other cardio-vascular parameters, thereby providing safe, effective, reliable and low cost monitoring of patie ...

2024

Modulation of Pulsatile Left Ventricular Afterload by Renal Denervation in Heart Failure With Preserved Ejection Fraction

Nikolaos Stergiopoulos, Stamatia Zoi Pagoulatou

Background:Arterial stiffening contributes to hemodynamic derangements in heart failure with preserved ejection fraction (HFpEF). We sought to investigate the impact of renal denervation on pulsatile left ventricular loading in patients with HFpEF and hype ...

Lippincott Williams & Wilkins2023

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions

Michaël Unser, Dimitris Perdios, Alexis Marie Frederic Goujon, Pakshal Narendra Bohra, Sebastian Jonas Neumayer, Stanislas Ducotterd

Lipschitz-constrained neural networks have several advantages over unconstrained ones and can be applied to a variety of problems, making them a topic of attention in the deep learning community. Unfortunately, it has been shown both theoretically and empi ...

2024

Optimizing Dynamic Aperture Studies with Active Learning

Tatiana Pieloni, Mike Seidel, Davide Di Croce, Ekaterina Krymova

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Iop Publishing Ltd2024

The Impact of Left Ventricular Performance and Afterload on the Evaluation of Aortic Valve Stenosis: A 1D Mathematical Modeling Approach

Nikolaos Stergiopoulos

The transaortic valvular pressure gradient (TPG) plays a central role in decision-making for patients suffering from severe aortic stenosis. However, the flow-dependence nature of the TPG makes the diagnosis of aortic stenosis challenging since the markers ...

MDPI2023

Compliance-matching vascular grafts with personalization potential

Georgios Rovas

Aortic diseases are characterized by dire prognosis and inadequate diagnosis, owing to their insidious yet lethal nature. Aortopathies, namely aortic aneurysms and dissections, along with certain congenital diseases, might necessitate surgical replacement ...

EPFL2023

Quantitative T2 Mapping of Acute Pancreatitis

Tom Hilbert

Background: Quantification of the T2 signal by means of T2 mapping in acute pancreatitis (AP) has the potential to quantify the parenchymal edema. Quantitative T2 mapping may overcome the limitations of previously reported scoring systems for reliable asse ...

Wiley2024

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Bénédicte Marie Maréchal, Ricardo Alberto Corredor Jerez

Background: Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and ...

Springernature2023

Wigner kernels: Body-ordered equivariant machine learning without a basis

Michele Ceriotti, Sergey Pozdnyakov, Filippo Bigi

Machine-learning models based on a point-cloud representation of a physical object are ubiquitous in scientific applications and particularly well-suited to the atomic-scale description of molecules and materials. Among the many different approaches that h ...

AIP Publishing2024

Integrated Electronics for Deep Implants to Remotely Monitor Hemodynamics

Mustafa Besirli

The integration of technology in the medical field has greatly improved accuracy in diagnoses, thus leading to more effective treatments. Wearable and implantable medical devices offer great potential for remote patient monitoring, particularly for heart f ...

EPFL2023