Back

Diagnostic and prognostic evaluation of an echocardiography-based artificial intelligence algorithm for detecting HFpEF: a case-control analysis

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

About the speaker

Photo
Doctor Alvin Chandra

UT Southwestern Medical Center, Dallas (United States of America)

7 More presentations in this session

Presentation thumbnail
Accurate detection of dilated cardiomyopathy onset through machine learning predictions from ECG data
Doctor E. Sieliwonczyk (Edegem, BE)
Abstract Slides Video
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

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
Performance of an automated echocardiographic artificial intelligence model. to detect subclinical heart failure with preserved ejection fraction (HFpEF) in community-dwelling older adults
thumbnail
Congress Presentation
Three rules to find them all: clinical risk scores in heart failure with preserved ejection fraction
thumbnail
Congress Presentation
Transfer learning for echocardiographic detection of heart failure with preserved ejection fraction: preliminary results of TALE-HFpEF Study

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources