Doctor Arnas Karuzas

Doctor Arnas Karuzas

Lithuanian University of Health Sciences, Kaunas (Lithuania)

Education: Public institution Franciscan gymnasium, secondary education, honors degree Lithuanian University of Health Sciences (LUHS), master degree in medicine, medicine doctor, honors degree Employment history: LUHS hospital Kaunas Clinics, Cardiology department, Cardiology resident, MD (2017-until now) LUHS Institute of physiology and pharmacology, Teaching assistant (2019-until now) LUHS Development department, project coordinator (2019-until now) Publications: Early and late diastolic strain rate vs global longitudinal strain at rest and during dobutamine stress for the assessment of significant coronary artery stenosis in patients with a moderate and high probability of coronary artery disease, Echocardiography. 1512-1522. DOI: 10.1111/echo.13282. Accuracy of three-dimensional systolic dyssynchrony and sphericity indexes for identifying early left ventricular remodeling after acute myocardial infarction, Anatol J Cardiol. 2019 Jun;22(1):13-20. doi: 10.14744.

Presentations

Automated evaluation of the left-sided heart volumes using machine learning during stress echocardiography: a multicenter stress echo 2030 study

Event: EACVI 2023

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Session: Artificial intelligence 2

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Deep learning for evaluating left atrium stress echocardiography: a proof of principle study

Event: ESC Congress 2022

Topic: Stress Echocardiography

Session: Advances in echocardiography technology

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Automated evaluation of the right-sided heart function and geometry using deep learning

Event: EACVI - Best of Imaging 2020

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

Session: ePoster session

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Accurate prediction of left ventricular diastolic dysfunction in 2D echocardiography using ensemble of deep convolutional neural networks

Event: ESC Congress 2020

Topic: Cardiovascular Image Processing

Session: e-Cardiology / Digital Health ePosters

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Deep learning in segmentation and function evaluation of right ventricle in 2D echocardiography

Event: EuroEcho 2019

Topic: Technology

Session: Artificial intelligence, deep-learning, 3D printing...what is the future of imaging?

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Artificial intelligence in echocardiography - Steps to automatic cardiac measurements in routine practice

Event: ESC Congress 2019

Topic: Cardiovascular Image Processing

Session: Remote patient monitoring and telemedicine

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The role of left ventricle myocardial regional deformation parameters during dobutamine stress to detect hemodynamically significant coronary artery stenoses

Event: EuroEcho-Imaging 2018

Topic: Stress Echocardiography

Session: Stress Echocardiography

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Left atrial deformation parameters for the assessment of hemodynamically significant coronary artery stenosis in patients with intermmediate pretest probability of coronary artery disease

Event: EuroEcho-Imaging 2017

Topic: Dobutamine stress echo

Session: Stress echo

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Global vs regional longitudinal strain at rest and during dobutamine stress for prediction of significant coronary artery stenosis

Event: ESC Congress 2016

Topic: Stress echo

Session: Best Posters in new observations in stress echocardiography

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Doctor Arnas Karuzas

Biography

Contributor content

Automated evaluation of the left-sided heart volumes using machine learning during stress echocardiography: a multicenter stress echo 2030 study

Deep learning for evaluating left atrium stress echocardiography: a proof of principle study

Automated evaluation of the right-sided heart function and geometry using deep learning

Accurate prediction of left ventricular diastolic dysfunction in 2D echocardiography using ensemble of deep convolutional neural networks

Deep learning in segmentation and function evaluation of right ventricle in 2D echocardiography

Artificial intelligence in echocardiography - Steps to automatic cardiac measurements in routine practice

The role of left ventricle myocardial regional deformation parameters during dobutamine stress to detect hemodynamically significant coronary artery stenoses

Left atrial deformation parameters for the assessment of hemodynamically significant coronary artery stenosis in patients with intermmediate pretest probability of coronary artery disease

Global vs regional longitudinal strain at rest and during dobutamine stress for prediction of significant coronary artery stenosis

ESC 365 is supported by

Doctor Arnas Karuzas Follow

Biography

Contributor content

Automated evaluation of the left-sided heart volumes using machine learning during stress echocardiography: a multicenter stress echo 2030 study

Deep learning for evaluating left atrium stress echocardiography: a proof of principle study

Automated evaluation of the right-sided heart function and geometry using deep learning

Accurate prediction of left ventricular diastolic dysfunction in 2D echocardiography using ensemble of deep convolutional neural networks

Deep learning in segmentation and function evaluation of right ventricle in 2D echocardiography

Artificial intelligence in echocardiography - Steps to automatic cardiac measurements in routine practice

The role of left ventricle myocardial regional deformation parameters during dobutamine stress to detect hemodynamically significant coronary artery stenoses

Left atrial deformation parameters for the assessment of hemodynamically significant coronary artery stenosis in patients with intermmediate pretest probability of coronary artery disease

Global vs regional longitudinal strain at rest and during dobutamine stress for prediction of significant coronary artery stenosis

ESC 365 is supported by

Doctor Arnas Karuzas