Back

Machine-learning integration of complex echocardiographic patterns and clinical parameters from cohorts and trials

2 September 2019 (16:57 - 17:06)
Organised by:
Congress Presentation Part of: Novel echocardiography techniques for heart failure Epidemiology, Prognosis, Outcome ESC Premium Access ESC Congress 2019

About the speaker

Photo
Professor Maja Cikes

University Hospital Centre Zagreb, Zagreb (Croatia)

7 More presentations in this session

Presentation thumbnail
Strain parameters at rest and after exercise in symptomatically stable patients with improved heart failure - STRESS-HF
Doctor M. Saran (Lucknow, IN)
Abstract Slides Video
Presentation thumbnail
Diastolic dysfunction is an independent predictor of adverse events in patients with systolic dysfunction. Insights from the MADIT-CRT trial
Doctor M. Gori (Bergamo, IT)
Abstract Slides Video
Presentation thumbnail
Revisiting the weber and ventilatory classifications in heart failure by combining exercise stress echo with gas exchange phenotyping
Doctor T. Sugimoto (Nagoya, JP)
Abstract Slides Video
Presentation thumbnail
Fast-SENC quantifies segmental right ventricular intramyocardial strain to assess subclinical RV dysfunction prior to changes in RV ejection fraction
Doctor M. Montenbruck (Hamburg, DE)
Abstract
Presentation thumbnail
The interrelation of left ventricular geometry with myocardial work
Doctor F. Sahiti (Wurzburg, DE)
Abstract

Access the full session

Session thumbnail
Novel echocardiography techniques for heart failure

The Event

Event poster

ESC Congress 2019

2 September 2019 16:57 CET

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources