Publications related to Active learning and margin strategies for arrhythmia classification in implantable devices

Related publications (15)

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Recent progress in computer vision has been driven by a simple yet transformative observation: the potential of 30-year-old neural networks can be unlocked by massively scaling their parameters and the amount of human-labeled training data. This breakthrou ...

EPFL2025

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

Minh Hieu Lê

Semi-supervised semantic segmentation methods leverage unlabeled data by pseudo-labeling them. Thus the success of these methods hinges on the reliability of the pseudo-labels. Existing methods mostly choose high-confidence pixels in an effort to avoid err ...

Springer Science and Business Media Deutschland GmbH2025

Personalized computational electro-mechanics simulations to optimize cardiac resynchronization therapy

Fabio Nobile

In this study, we present a computational framework designed to evaluate virtual scenarios of cardiac resynchronization therapy (CRT) and compare their effectiveness based on relevant clinical biomarkers. Our approach involves electro-mechanical numerical ...

2024

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

Artificial Intelligence for road quality assessment in smart cities: a machine learning approach to acoustic data analysis

Simon Elias Bibri

In smart cities, ensuring road safety and optimizing transportation efficiency heavily relies on streamlined road condition monitoring. The application of Artificial Intelligence (AI) has notably enhanced the capability to detect road surfaces effectively. ...

Springernature2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

Heart Energy Harvesting and Cardiac Bioelectronics: Technologies and Perspectives

Massimo Mariello

Nanogenerators are a recently emerging technology which is able to cost-effectively harvest energy from renewable and clean energy sources at the micro/nano-scale. Their applications in the field of self-powered sensing systems and portable power supplying ...

MDPI2022

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Stefano Pagani, Riccardo Tenderini

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

2022

Does one size fit all? - Towards the optimization and personalization of non-invasive brain stimulation paradigms to enhance motor learning

Laurijn Rianne Draaisma

The acquisition and re-acquisition of motor skills is an important aspect of daily life and in the recovery after a stroke. Non-invasive brain stimulation (NIBS) is a technique that is used to improve motor learning and enhance motor recovery in stroke sur ...

EPFL2022

POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium

Alfio Quarteroni, Andrea Manzoni

The numerical simulation of multiple scenarios easily becomes computationally prohibitive for cardiac electrophysiology (EP) problems if relying on usual high-fidelity, full order models (FOMs). Likewise, the use of traditional reduced order models (ROMs) ...

FRONTIERS MEDIA SA2021

The effect of left ventricular contractility on arterial hemodynamics: A model-based investigation

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Stamatia Zoi Pagoulatou

Ventricular-arterial coupling is a major determinant of cardiovascular performance, however, there are still inherent difficulties in distinguishing ventricular from vascular effects on arterial pulse phenotypes. In the present study, we employed an extens ...

2021

Uncertainty Reduction for Model Adaptation in Semantic Segmentation

François Fleuret, Prabhu Teja Sivaprasad

Traditional methods for Unsupervised Domain Adaptation (UDA) targeting semantic segmentation exploit information common to the source and target domains, using both labeled source data and unlabeled target data. In this paper, we investigate a setting wher ...

IEEE2021

Embedding Mobile Health Technology into the Nurses' Health Study 3 to Study Behavioral Risk Factors for Cancer

Christine Choirat

Background: Physical activity and sleep are behavioral risk factors for cancer that may be influenced by environmental exposures, including built and natural environments. However, many studies in this area are limited by residence-based exposure assessmen ...

2020

Heart Rhythm Classification using Short-term ECG Atrial and Ventricular Activity Analysis

Jean-Marc Vesin, Sasan Yazdani, Adrian Luca

2017

Study of the impact of electrical heterogeneities in the right and left atrium on atrial fibrillation perpetuation

Jean-Marc Vesin, Vincent Jacquemet, Adrian Luca

Introduction: Electrical heterogeneity in the atria has been consistently linked with the initiation and perpetuation of atrial fibrillation (AF). The present model-based study investigated the contribution of action potential duration (APD) heterogeneitie ...

Oxford Univ Press2016