Back

Predicting ECGs masquerading AS STEMI with machine learning

1 September 2024 (10:00 - 10:50)
Organised by: Logo
Congress Presentation Part of: Biomarkers and machine learning in acute coronary syndromes: pathways to precision diagnosis and stratification ST-Elevation Myocardial Infarction (STEMI) ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

Photo
Doctor Sina Fathieh

Imperial College London, London (United Kingdom of Great Britain & Northern Ireland)

7 More presentations in this session

Presentation thumbnail
Incidence of MINOCA in the high-sensitivity troponin era: a meta-analysis
Doctor P. Mikhail (Gosford, AU)
Abstract Slides Video
Presentation thumbnail
External validation of a stepwise 0/1/3h algorithm to triage patients with suspected myocardial infarction
Doctor J. Lehmacher (Hamburg, DE)
Abstract Slides Video
Presentation thumbnail
Multi-biomarker approach for predicting cardiac magnetic resonance parameters at 30 days after ST-segment elevation myocardial infarction
Professor R. Klingenberg (Frankfurt, DE)
Abstract Slides Video
Presentation thumbnail
Safety and efficiency of modified HEART scores without troponin or electrocardiography: an analysis based on two European out-of-hours primary care cohorts
Miss I. Melessen (Amsterdam, NL)
Abstract Slides Video
Presentation thumbnail
Comparing predictive risk to actual presence of coronary atherosclerosis on coronary computed tomography angiography: a retrospective cohort analysis
Professor S. Stewart (Fremantle, AU)
Abstract Slides Video

Access the full session

Session thumbnail
Biomarkers and machine learning in acute coronary syndromes: pathways to precision diagnosis and stratification

The Event

Event poster

ESC Congress 2024

1 September 2024 10:00 CET
You may be interested in
thumbnail
Congress Presentation
Can prediction of acute myocardial infarction using a deep learning-enabled electrocardiogram be used in real-world practice?
thumbnail
Congress Presentation
External validation of the ECG-SMART model: a machine learning algorithm for ECG diagnosis of occlusion myocardial infarction
thumbnail
Congress Presentation
Validation of an artificial intelligence model for occlusion myocardial infarction identification: initial findings from a Portuguese cohort

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources