Publications related to Estimation of Left Ventricular End-Systolic Elastance From Brachial Pressure Waveform via Deep Learning

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

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, Georgios Rovas, Sokratis Anagnostopoulos, Vasiliki Bikia, Patrick Segers

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

Partial discharge localization in power transformer tanks using machine learning methods

Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

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

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Alfio Quarteroni, Francesco Regazzoni, Luca Dede'

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

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen, Michele Bianco

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

David Atienza Alonso, José Angel Miranda Calero, Jonathan Dan, Christodoulos Kechris

Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they often un ...

2024

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Estimation of Left Ventricular End-Systolic Elastance From Brachial Pressure Waveform via Deep Learning

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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

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

Partial discharge localization in power transformer tanks using machine learning methods

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

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

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

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

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Partial discharge localization in power transformer tanks using machine learning methods

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

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning