Back

Clinical Turing tests with user certainty analysis to create and validate synthetic electrocardiogram images for artificial intelligence-enhanced algorithm development

7 April 2024 (09:30 - 10:15)
Organised by: Logo
Congress Presentation Part of: eCardiology 1 Artificial Intelligence EHRA Premium Access EHRA 2024 European Heart Rhythm Association (EHRA)

About the speaker

Photo
Doctor Neil Bodagh

King's College London, London (United Kingdom of Great Britain & Northern Ireland)

8 More presentations in this session

Presentation thumbnail
Changes in public interest in sudden cardiac arrest: a big data analysis
Doctor J. Han (Los Angeles, US)
Abstract Slides Video
Presentation thumbnail
Results of external validation for anatomical site recognition of ablation sites in atrial fibrillation using the CARTONET R12 model
Assistant Professor W. sasaki (Hidaka, JP)
Abstract Slides Video
Presentation thumbnail
Artificial intelligence-estimated electrocardiographic age as a recurrence predictor after atrial fibrillation catheter ablations
Doctor H. Park (Seoul, KR)
Abstract Slides Video
Presentation thumbnail
Twelve-lead electrocardiography-based artificial intelligence predicts the upcoming future of patients with heart failure with mildly reduced ejection fraction
Mr S. Lee (Incheon, KR)
Abstract Slides Video
Presentation thumbnail
Recognition of Brugada type 1 pattern on ECG by Echo State Networks
Mr F. Vozzi (Pisa, IT)
Abstract Slides Video

Access the full session

Session thumbnail
eCardiology 1

The Event

Event poster

EHRA 2024

7 April 2024 09:30 CET
You may be interested in
thumbnail
Congress Presentation
Using AI to read behind the ECG traces
thumbnail
Congress Presentation
Diagnostic performance of an artificial intelligence-based electrocardiogram interpretation system for acute coronary occlusion in adults following out-of-hospital cardiac arrest
thumbnail
Congress Presentation
Generative adversarial networks (GANs) to produce synthetic 12-lead electrocardiogram signals for specific and rare diseases: a novel, powerful tool towards clinical advancements

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources