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Machine-learning algorithms for prediction of survival by stress echocardiography in chronic coronary syndromes

27 August 2022 (09:50 - 10:00)
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Congress Presentation Part of: Echocardiography in acute and chronic coronary syndromes Stress Echocardiography ESC Professional Premium Access ESC Congress 2022

About the speaker

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Doctor Nicola Gaibazzi

University Hospital of Parma, Parma (Italy)

5 More presentations in this session

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Prognostic value of coronary flow and heart rate reserve in emergency department chest pain
Doctor A. Vecchi (Livorno, IT)
Abstract Slides Video
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Diastolic stress echocardiography in patients with normal resting diastolic function: prognostic utility in presence and absence of myocardial ischemia
Doctor L. Alam (New York City, US)
Abstract Slides Video
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High resting coronary flow velocity predicts worse survival in chronic coronary syndromes
Doctor N. Gaibazzi (Parma, IT)
Abstract Slides Video
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Clinical significance of myocardial work parameters after acute myocardial infarction
Associate Professor A. Coisne (Lille, FR)
Abstract Slides Video
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Left atrial strain analysis improves non-invasive estimation of left ventricular filling pressures in takotsubo syndrome
Doctor G. Iannaccone (Rome, IT)
Abstract Slides Video

Access the full session

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Echocardiography in acute and chronic coronary syndromes

The Event

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ESC Congress 2022

27 August 2022 09:50 CET
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novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources