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

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About the speaker

Associate Professor Maja Cikes

University Hospital Centre Zagreb, Zagreb (Croatia)

57 presentations

18 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 (Nagoya, 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

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