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

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

Session: Novel echocardiography techniques for heart failure

Topic: Epidemiology, Prognosis, Outcome

Speaker: Associate Professor M. Cikes (Zagreb, HR)

Event: ESC Congress 2019

Congress Presentation

About the speaker

Associate Professor Maja Cikes

University Hospital Centre Zagreb, Zagreb (Croatia)

37 presentations

9 followers

7 more presentations in this session

Strain parameters at rest and after exercise in symptomatically stable patients with improved heart failure - STRESS-HF

Speaker: Doctor M. Saran (Lucknow, IN)

Diastolic dysfunction is an independent predictor of adverse events in patients with systolic dysfunction. Insights from the MADIT-CRT trial

Speaker: Doctor M. Gori (Bergamo, IT)

Revisiting the weber and ventilatory classifications in heart failure by combining exercise stress echo with gas exchange phenotyping

Speaker: Doctor T. Sugimoto (Tsu, JP)

Fast-SENC quantifies segmental right ventricular intramyocardial strain to assess subclinical RV dysfunction prior to changes in RV ejection fraction

Speaker: Doctor M. Montenbruck (Hamburg, DE)

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Abstract

The interrelation of left ventricular geometry with myocardial work

Speaker: Doctor F. Sahiti (Wurzburg, DE)

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Abstract

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Novel echocardiography techniques for heart failure

Speakers: Associate Professor M. Cikes, Doctor M. Saran, Doctor M. Gori, Doctor T. Sugimoto, Doctor M. Montenbruck...

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About the event

ESC Congress 2019

31 August - 4 September 2019

Sessions Presentations

Congress

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

About the speaker

Associate Professor Maja Cikes

7 more presentations in this session

Strain parameters at rest and after exercise in symptomatically stable patients with improved heart failure - STRESS-HF

Diastolic dysfunction is an independent predictor of adverse events in patients with systolic dysfunction. Insights from the MADIT-CRT trial

Revisiting the weber and ventilatory classifications in heart failure by combining exercise stress echo with gas exchange phenotyping

Fast-SENC quantifies segmental right ventricular intramyocardial strain to assess subclinical RV dysfunction prior to changes in RV ejection fraction

The interrelation of left ventricular geometry with myocardial work

Access the full session

Novel echocardiography techniques for heart failure

About the event

ESC Congress 2019

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