Machine-learning based scoring system to predict cardiogenic shock in acute coronary syndrome

30 August 2024 (14:35 - 14:47)

Organised by:

Video

Sign in for access options

Slides

About the speaker

Associate Professor Allan Bohm

Premedix & Seerlinq, Bratislava (Slovakia)

5 More presentations in this session

Presentation thumbnail

Artificial intelligence-based prediction of mortality, bleeding, and ischaemic events in cancer patients with acute coronary syndrome: A modelling study in the UK and Switzerland

Doctor F. Wenzl (Zurich, CH)

Presentation thumbnail

Artificial intelligence for analysis of ambulatory electrocardiography

Doctor L. Johnson (Malmo, SE)

Presentation thumbnail

Heart Failure detection using Artificial Intelligence for diagnostic decision support applied to echocardiography - HFDetect-AI

Professor G. Strange (Sydney, AU)

Presentation thumbnail

MitrAI score: machine learning models to predict mortality at 12, 24, 36 and 48 months in patients with primary and secondary mitral regurgitation treated by transcatheter edge-to-edge repair.

Doctor L. Biasco (Cirie, IT)

Presentation thumbnail

Machine learning algorithm using point-of-care high-sensitivity cardiac troponin I for rapid rule-out of myocardial infarction

Doctor B. Toprak (Hamburg, DE)

Access the full session

Session thumbnail

Registries, observational, and other studies on artificial intelligence

The Event

Event poster

ESC Congress 2024

30 August 2024 14:35 CET

You may be interested in

Congress Presentation

Machine learning to predict cardiogenic shock in acute coronary syndrome

Congress Session

Registries, observational, and other studies on artificial intelligence

Congress Presentation

Hybrid machine learning pipeline for multi-timeframe mortality prediction in cardiogenic shock: integrating clustering techniques and comprehensive external validation

ESC 365 is supported by

novartis

Explore sponsored resources

ESC 365 is supported by

novartis

Explore sponsored resources