Doctor Aurore Lyon

Doctor Aurore Lyon

Cardiovascular Research Institute Maastricht (CARIM), Maastricht (Netherlands (The))

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Dr Aurore Lyon graduated from Telecom ParisTech Engineering School in Paris (France) with a Master in Engineering, and from the University of Oxford (UK) with a Master in Computer Science. She obtained her PhD in the Computational Cardiovascular Science group (University of Oxford). Her PhD focussed on using computational techniques for analysis, modelling and simulation of ECG signals for patient risk stratification in hypertrophic cardiomyopathy. Since April 2018, she has been working at Maastricht University. Her current research focusses on cardiac electromechanics and the coupling from cellular electrophysiology to whole-heart mechanics and hemodynamics. Specific projects of research include electromechanical modelling, effect of exercise on cardiac pathologies such as ARVC or deformation imaging analysis in atrial fibrillation patients. Her interests lie in combining computer simulations with clinical data to better understand cardiac physiology or disease mechanisms.

Presentations Articles

Computational modeling identifies the cellular electromechanical effects of disrupted intracellular calcium handling in arrhythmogenic cardiomyopathy patients

Event: Frontiers in CardioVascular Biomedicine 2022

Topic: Cardiomyopathies

Session: Semmelweis University Moderated Poster Award session

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Computational modeling identifies the cellular electromechanical effects of disrupted intracellular calcium handling in arrhythmogenic cardiomyopathy patients

Event: EHRA 2022

Topic: Cardiac Diseases

Session: ePosters Day 3

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Development of a multiscale electromechanical computer model from cell to hemodynamics

Event: EHRA 2021

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Session: WGCCE

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Synergy between data and knowledge-based models: the hybrid artificial intelligence approach.

Event: ESC Congress 2020

Topic: Hospital Information Systems, Electronic Medical Records, Clinical Decision Support

Session: The Digital Twin: a Mirror for Personalized Medicine

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Irregular beat-to-beat hemodynamic properties determine left ventricular function during atrial fibrillation

Event: ESC Congress 2020

Topic: Pathophysiology and Mechanisms

Session: Atrial Fibrillation ePosters

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Differentiating the exercise-induced effects of acute beta-adrenergic stimulation and stretch on calcium and force dynamics using a novel electromechanical cardiomyocyte model

Event: EHRA 2019

Topic: e-Cardiology/Digital Health, Other

Session: Intracellular calcium (dys)regulation and cardiac remodeling

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Redefining risk with Artificial Intelligence.

Event: CMR 2018 (the 5th joint EuroCMR/SCMR meeting)

Topic: Cardiac Magnetic Resonance (CMR)

Session: Lecture Session 2 - Machine Learning Artificial Intelligence and Post Processing

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Risk stratification in hypertrophic cardiomyopathy based on QRS and T wave morphological biomarkers identifies three phenotypic subgroups.

Event: ESC Congress 2016

Topic: ECG and arrhythmia analysis

Session: ECG, arrhythmia analysis, cardiovascular signal processing

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Doctor Aurore Lyon

Biography

Contributor content

Computational modeling identifies the cellular electromechanical effects of disrupted intracellular calcium handling in arrhythmogenic cardiomyopathy patients

Computational modeling identifies the cellular electromechanical effects of disrupted intracellular calcium handling in arrhythmogenic cardiomyopathy patients

Development of a multiscale electromechanical computer model from cell to hemodynamics

Synergy between data and knowledge-based models: the hybrid artificial intelligence approach.

Irregular beat-to-beat hemodynamic properties determine left ventricular function during atrial fibrillation

Differentiating the exercise-induced effects of acute beta-adrenergic stimulation and stretch on calcium and force dynamics using a novel electromechanical cardiomyocyte model

Redefining risk with Artificial Intelligence.

Risk stratification in hypertrophic cardiomyopathy based on QRS and T wave morphological biomarkers identifies three phenotypic subgroups.

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