ESC 365 - Improving prognostic accuracy in ischemic cardiomyopathy: the CMR-LGE score

ESC Professional Premium Access

Improving prognostic accuracy in ischemic cardiomyopathy: the CMR-LGE score

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

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Doctor A. Unger (Brussels, BE)

Event: ESC Congress 2024

Congress Presentation

Add to my library

About the speaker

Doctor Alexandre Unger

Erasme Academic Hospital – Université Libre De Bruxelles (Ulb), Brussels (Belgium)

0 follower

8 more presentations in this session

Identifying at-risk patients for atrial high-rate episodes by machine learning

Speaker: Doctor Y. Chen (Liverpool, GB)

Improving cardiovascular risk stratification with ECG-predicted risk factors in primary prevention

Speaker: Mr M. Knorr (Hamburg, DE)

Time-series clustering of raw recordings of 24-hour ambulatory blood presssure for risk stratification in general population

Speaker: Mr E. Ntalianis (Leuven, BE)

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

Speaker: Doctor E. Ronner (Delft, NL)

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

Speaker: Doctor Y. Bitton (Jerusalem, IL)

Access the full session

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

Speakers: Doctor A. Unger, Doctor Y. Chen, Mr M. Knorr, Mr E. Ntalianis, Doctor E. Ronner...

About the event

ESC Congress 2024

30 August - 2 September 2024

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources

Explore sponsored resources