Publications associées à AI-Based Estimation of End-Systolic Elastance From Arm-Pressure and Systolic Time Intervals

Publications associées (42)

Lumped Parameter Modeling of the Hypoplastic Left Heart Syndrome During Birth

Hypoplastic left heart syndrome (HLHS) is a congenital heart disease characterized by the underdevelopment of left heart structures. Previous studies using lumped-parameter models focused on extreme cases where the left ventricle is absent. We propose a mo ...

Springer Science and Business Media Deutschland GmbH2025

Minimally Invasive and in Situ Capacitive Sensing of Cardiac Troponin I From Interstitial Fluid

Hadi Mirzajani

Current diagnostic approaches for myocardial infarction (MI) rely on blood-based cardiac biomarker analysis by centralized instruments, often delaying timely clinical decisions. We present a microneedle-based capacitive biosensor (MiCaP) for in situ minima ...

AMER CHEMICAL SOC2025

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

Zeki Doruk Erden

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

EPFL2025

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

Zaffar Ahmed Shaikh

As one of the major threats to women's health worldwide, breast cancer requires early diagnosis and accurate classification, since they are key to optimizing therapeutic interventions and ensuring precise prognosis. Recently, deep learning has demonstrated ...

SAGE PUBLICATIONS LTD2025

Learning to Assemble with Alternative Plans

Gabriel Rémi Vallat, Maryam Kamgarpour, Stefana Parascho, Ziqi Wang, Jingwen Wang

We present a reinforcement learning framework for constructing assemblies composed of rigid parts, which are commonly seen in many historical masonry buildings and bridges. Traditional construction methods for such structures often depend on dense scaffold ...

Association for Computing Machinery (ACM)2025

Improving the accuracy and interpretability of neural networks for wind power forecasting

Fernando Porté Agel, Jiannong Fang, Wenlong Liao

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

2025

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

How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks

Volkan Cevher, Fanghui Liu, Zhenyu Zhu

This paper investigates the fundamental regression task of learning k neurons (a.k.a. teachers) from Gaussian input, using two-layer ReLU neural networks with width m (a.k.a. students) and m, k = O(1), trained via gradient descent under proper initializati ...

2025

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

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Neha Tarigopula

Sign Language conveys information through multiple channels composed of manual (handshape, hand movement) and non-manual (facial expression, mouthing, body posture) components. Sign language assessment involves giving granular feedback to a learner, in ter ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Hemodynamic effects of a dielectric elastomer augmented aorta on aortic wave intensity: An in-vivo study

Yves Perriard, Yoan René Cyrille Civet, Thomas Guillaume Martinez, Armando Matthieu Walter, Francesco Clavica, Silje Ekroll Jahren

Dielectric elastomer actuator augmented aorta (DEA) represents a novel approach with high potential for assisting a failing heart. The soft tubular device replaces a section of the aorta and increases its diameter when activated. The hemodynamic interactio ...

2023

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

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

Effect of the structural modification of Candesartan with Zinc on hypertension and left ventricular hypertrophy

Nikolaos Stergiopoulos, Augusto Martins Lima

Hypertension is the most common cause of left ventricular hypertrophy, contributing to heart failure progression. Candesartan (Cand) is an angiotensin receptor antagonist widely used for hypertension treatment. Structural modifications were previously perf ...

ELSEVIER2023

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

On the similarity between aortic and carotid pressure diastolic decay: a mathematical modelling study

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Aortic diastolic pressure decay (DPD) has been shown to have considerable pathophysiological relevance in the assessment of vascular health, as it is significantly affected by arterial stiffening. Nonetheless, the aortic pressure waveform is rarely availab ...

Nature Portfolio2023

Arterial pulse wave modeling and analysis for vascular-age studies: a review from VascAgeNet

Vasiliki Bikia

Arterial pulse waves (PWs) such as blood pressure and photoplethysmogram (PPG) signals contain a wealth of information on the cardiovascular (CV) system that can be exploited to assess vascular age and identify individuals at elevated CV risk. We review th ...

AMER PHYSIOLOGICAL SOC2023

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

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas

Background: Cardiac output is essential for patient management in critically ill patients. The state-of-the-art for cardiac output monitoring bears limitations that pertain to the invasive nature of the method, high costs, and associated complications. Hen ...

FRONTIERS MEDIA SA2023

Causal inference with recurrent and competing events

Mats Julius Stensrud, Pal Christie Ryalen, Matias Janvin

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

SPRINGER2023

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Clémentine Léa Aguet

Blood pressure (BP) is a crucial indicator of cardiovascular health. Hypertension is a common life-threatening condition and a key factor of cardiovascular diseases (CVDs). Identifying abnormal BP fluctuations can allow for early detection and management o ...

EPFL2023