Back

Accurate detection of dilated cardiomyopathy onset through machine learning predictions from ECG data

30 August 2024 (08:00 - 17:30)
Organised by: Logo
Congress Presentation Part of: Machine-learning approaches for the diagnosis of heart failure Diagnostic Methods ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

Photo
Doctor Ewa Sieliwonczyk

University Hospital Antwerp, Edegem (Belgium)

7 More presentations in this session

Presentation thumbnail
Long-term clinical outcomes informed by artificial intelligence-enabled single-lead ECG detection of reduced ejection fraction
Mr A. Alrumayh (London, GB)
Abstract Slides Video
Presentation thumbnail
Machine learning methods for diagnostic disease prediction and treatment decisions in parvovirus B19 positive viral cardiomyopathy
Doctor C. Baumeier (Berlin, DE)
Abstract Slides Video
Presentation thumbnail
Construction of an inflammatory, nutritional, and metabolic prognostic risk score in patients with heart failure with preserved ejection fraction: a machine learning-based approach
Doctor J. Feng (Singapore, SG)
Abstract Slides Video
Presentation thumbnail
Artificial intelligence to detect pulmonary congestion on chest computed tomography in consecutive dyspnoeic patients
Professor O. Nielsen (Copenhagen, DK)
Abstract Slides Video
Presentation thumbnail
Diagnostic and prognostic evaluation of an echocardiography-based artificial intelligence algorithm for detecting HFpEF: a case-control analysis
Assistant Professor A. Chandra (Dallas, US)
Abstract Slides Video

Access the full session

Session thumbnail
Machine-learning approaches for the diagnosis of heart failure

The Event

Event poster

ESC Congress 2024

30 August - 2 September 2024
You may be interested in
thumbnail
Congress Presentation
Artificial intelligence for prediction of major arrhythmic events in dilated cardiomyopathy
thumbnail
Congress Presentation
Precision phenotyping, prognostication, and drug response prediction of dilated cardiomyopathy using serum proteomic data
thumbnail
Congress Presentation
Utility of polygenic risk score for prediction of dilated cardiomyopathy and modulation of severity of LV dysfunction among cases

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources