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A machine learning method for real-time numerical simulations of cardiac electromechanics

Computer methods in applied mechanics and engineering, 2022-04, Vol.393, p.114825, Article 114825

2022

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Machine learning for fast and reliable solution of time-dependent differential equations

Journal of computational physics, 2019-11, Vol.397, p.108852, Article 108852

2019

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Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics

Computer methods in applied mechanics and engineering, 2020-10, Vol.370, p.113268, Article 113268

2020

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SUIHTER: a new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy

Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences, 2021-09, Vol.477 (2253), p.20210027-20210027

2021

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Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks

Computers & mathematics with applications (1987), 2021-12, Vol.104, p.1-13

2021

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A cardiac electromechanical model coupled with a lumped-parameter model for closed-loop blood circulation

Journal of computational physics, 2022-05, Vol.457, p.111083, Article 111083

2022

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Fluid dynamics of an idealized left ventricle: the extended Nitsche's method for the treatment of heart valves as mixed time varying boundary conditions

International journal for numerical methods in fluids, 2017-09, Vol.85 (3), p.135-164

2017

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A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

Frontiers in physiology, 2021-07, Vol.12, p.673612-673612

2021

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Optimal flow control for Navier-Stokes equations: drag minimization

International journal for numerical methods in fluids, 2007-10, Vol.55 (4), p.347-366

DEDE, L

2007

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High Outpatient Attendance During COVID‐19 Lockdown When Patients Were Given the Option to Return

Movement disorders, 2020-12, Vol.35 (12), p.2137-2138

2020

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Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease

Frontiers in neurology, 2021-09, Vol.12, p.704906-704906

2021

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Introduction to Cognitive Restructuring for Medical Students

MedEdPORTAL, 2022, Vol.18, p.11235-11235

2022

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B-spline goal-oriented error estimators for geometrically nonlinear rods

Computational mechanics, 2012, Vol.49 (1), p.35-52

2012

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Segregated Algorithms for the Numerical Simulation of Cardiac Electromechanics in the Left Human Ventricle

The Mathematics of Mechanobiology, 2020, Vol.2260, p.81-116

2020

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Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications

1, 2019

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A matrix–free high–order solver for the numerical solution of cardiac electrophysiology

Journal of computational physics, 2023-04, Vol.478, p.111984, Article 111984

2023

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Fathering in Cultural Contexts: Developmental and Clinical Issues

1, 2019

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3282Evaluation of blood flow patterns for personalized stroke risk assessment in atrial fibrillation

European heart journal, 2018-08, Vol.39 (suppl_1)

2018

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Abstract 5110: Runx knockout in breast luminal stem/progenitor cells induced precancerous lesion via robust expression of ERα

Cancer research (Chicago, Ill.), 2018-07, Vol.78 (13_Supplement), p.5110-5110

2018

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CLIMATIC EFFECTS ON THE PHENOLOGY OF GEOPHYTES

Applied ecology and environmental research, 2009-01, Vol.7 (3), p.253-266

Eppich, B

2009

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590Development of a patient-specific computational fluid dynamics model of the LA in AF for stroke risk assessment

Europace (London, England), 2017-06, Vol.19 (suppl_3), p.iii120-iii121

2017

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Parameter estimation from clinical data

Mathematical Modelling of the Human Cardiovascular System, 2019, p.178-202

2019

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Basic facts on quantitative cardiac physiology

Mathematical Modelling of the Human Cardiovascular System, 2019, p.79-91

2019

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An insight into vascular data

Mathematical Modelling of the Human Cardiovascular System, 2019, p.10-24

2019

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An insight into cardiac data

Mathematical Modelling of the Human Cardiovascular System, 2019, p.92-101

2019

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A machine learning method for real-time numerical simulations of cardiac electromechanics

Machine learning for fast and reliable solution of time-dependent differential equations

Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics

SUIHTER: a new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy

Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks

A cardiac electromechanical model coupled with a lumped-parameter model for closed-loop blood circulation

Fluid dynamics of an idealized left ventricle: the extended Nitsche's method for the treatment of heart valves as mixed time varying boundary conditions

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

Optimal flow control for Navier-Stokes equations: drag minimization

High Outpatient Attendance During COVID‐19 Lockdown When Patients Were Given the Option to Return

Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease

Introduction to Cognitive Restructuring for Medical Students

B-spline goal-oriented error estimators for geometrically nonlinear rods

Segregated Algorithms for the Numerical Simulation of Cardiac Electromechanics in the Left Human Ventricle

Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications

A matrix–free high–order solver for the numerical solution of cardiac electrophysiology

Fathering in Cultural Contexts: Developmental and Clinical Issues

3282Evaluation of blood flow patterns for personalized stroke risk assessment in atrial fibrillation

Abstract 5110: Runx knockout in breast luminal stem/progenitor cells induced precancerous lesion via robust expression of ERα

CLIMATIC EFFECTS ON THE PHENOLOGY OF GEOPHYTES

590Development of a patient-specific computational fluid dynamics model of the LA in AF for stroke risk assessment

Parameter estimation from clinical data

Basic facts on quantitative cardiac physiology

An insight into vascular data

An insight into cardiac data

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