ESC 365 - Doctor Marton Tokodi

Speaker illustration

Doctor Marton Tokodi

Semmelweis University, Budapest (Hungary)

Member of:

Heart Failure Association

Presentations Articles

Machine learning-based mortality prediction in patients undergoing CRT implantation using the SEMMELWEIS-CRT score: validation in the European CRT survey I database

Event: Heart Failure 2024

Topic: Cardiac Resynchronisation Therapy (CRT)

Session: Arrhythmias & device

Prognostic value of right ventricular mechanical pattern assessed with 3D echocardiography in patients with left-sided heart disease

Event: EACVI - Best of Imaging 2020

Topic: 3D Echocardiography

Session: Live Abstract Presentations - Right ventricular

Pursuing the non-invasive assessment of cardiac contractility: the added value of pressure-area-strain loop analysis in volume overload-induced heart failure

Event: EACVI - Best of Imaging 2020

Topic: Tissue Doppler, Speckle Tracking and Strain Imaging

Session: Young Investigator Award session - Basic Science

Myocardial work of the athlete's heart: the new champion of systolic function?

Event: ESC Congress 2020

Topic: Systolic and Diastolic Function

Session: Myocardial Work by Echocardiography: a New Insight into Left Ventricular Function

Exploring sex-specific patterns of mortality predictors among patients undergoing cardiac resynchronization therapy: A machine learning approach

Event: ESC Congress 2020

Topic: Epidemiology, Prognosis, Outcome

Session: Chronic Heart Failure ePosters

Perioperative shift in right ventricular mechanical pattern in patients undergoing mitral valve surgery: a predictor of right ventricular failure?

Event: ESC Congress 2019

Topic: Mitral Valve Regurgitation

Session: Mitral and tricuspid valve regurgitation: new insights

Survival prediction in patients undergoing cardiac resynchronization therapy: a machine learning based risk stratification system

Event: ESC Congress 2019

Topic: Big Data and Digital Twin

Session: Machine learning - State of the art

ReVISION – Right VentrIcular Separate wall motIon quantificatiON

Event: ESC Congress 2019

Topic: IMAGING

Session: Data Analysis

Machine learning based risk stratification of patients undergoing cardiac resynchronization therapy

Event: Heart Failure 2019

Topic: Cardiac Resynchronisation Therapy (CRT)

Session: Rapid Fire 6 - Risk stratification and prognosis

Machine learning for recognition of athlete's heart using 3D volumetric and motion analysis of the right ventricle

Event: EuroEcho-Imaging 2018

Topic: 3D Echocardiography

Session: 3D Echocardiography

ESC 365 is supported by

Explore sponsored resources

Explore sponsored resources