Back

AI-based cluster analysis enables outcomes prediction among patients with increased LVM

30 August 2024 (08:00 - 17:30)
Organised by: Logo
Congress Presentation Part of: Artificial intelligence-powered cardiovascular risk assessment: machine learning for disease detection Artificial Intelligence ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

Photo
Associate Professor Yitschak Bitton

Hadassah - Hebrew University Medical Center Jerusalem, Jerusalem (Israel)

8 More presentations in this session

Presentation thumbnail
Identifying at-risk patients for atrial high-rate episodes by machine learning
Doctor Y. Chen (Liverpool, GB)
Abstract Slides Video
Presentation thumbnail
Improving cardiovascular risk stratification with ECG-predicted risk factors in primary prevention
Mr M. Knorr (Hamburg, DE)
Abstract Slides Video
Presentation thumbnail
Improving prognostic accuracy in ischemic cardiomyopathy: the CMR-LGE score
Doctor A. Unger (Brussels, BE)
Abstract Slides Video
Presentation thumbnail
Time-series clustering of raw recordings of 24-hour ambulatory blood presssure for risk stratification in general population
Mr E. Ntalianis (Leuven, BE)
Abstract Slides Video
Presentation thumbnail
To compare 24 hour blood pressure values of a conventional 24 hours ambulatory blood pressure device versus a wristband using an artificial intelligence algorithm based on photophletysmography
Doctor E. Ronner (Delft, NL)
Abstract Slides Video

Access the full session

Session thumbnail
Artificial intelligence-powered cardiovascular risk assessment: machine learning for disease detection

The Event

Event poster

ESC Congress 2024

30 August - 2 September 2024
You may be interested in
thumbnail
Congress Presentation
Clinical phenotypes in relation to outcomes in heart failure patients with cardiac resynchronization therapy and defibrillators (CRT-D): an unsupervised cluster analysis
thumbnail
Congress Presentation
Mortality-based clustering reveals distinct subgroups in heart failure with preserved ejection fraction
thumbnail
Congress Presentation
Diagnostic and prognostic value of ECG-predicted hypertension mediated left ventricular hypertrophy using machine learning

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources