ESC 365 - Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI

ESC Premium Access

Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI

Session: Digital tools to inform decisions in aortic stenosis

Topic: Aortic Valve Stenosis

Speaker: Professor B. Meder (Heidelberg, DE)

Event: ESC Congress 2024

Congress Presentation

About the speaker

Professor Benjamin Meder

University Hospital Heidelberg, Heidelberg (Germany)

12 presentations

1 follower

2 more presentations in this session

Deep learning to predict progression of aortic stenosis

Speaker: Doctor E. Oikonomou (New Haven, US)

TAVI vs. SAVR: a decision model

Speaker: Professor S. Bleiziffer (Bad Oeynhausen, DE)

Access the full session

Digital tools to inform decisions in aortic stenosis

Speakers: Professor B. Meder, Doctor E. Oikonomou, Professor S. Bleiziffer

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