Predicting ventricular tachycardia in post-MI patients years in advance using artificial intelligence on ECGs

Back

ESC2025 Premium Access

Predicting ventricular tachycardia in post-MI patients years in advance using artificial intelligence on ECGs

Session: Artificial intelligence in cardiology: transforming ECG analysis for precision care

Topic: Deep Learning

Speaker: Miss C. Buck (Eindhoven, NL)

Event: ESC Congress 2025

Congress Presentation

Add to my library

About the speaker

Miss Carlijn Maureen Arthure Buck

Eindhoven University of Technology, Eindhoven (Netherlands (The))

0 follower

7 more presentations in this session

Performance of a deep learning ECG model in predicting atrial fibrillation among patients with implantable loop recorders

Speaker: Doctor A. Estrada-Magana (Rochester, US)

Machine-learning based ECG model to differentiate takotsubo syndrome from myocardial infarction

Speaker: Doctor H. Hakansson (Stockholm, SE) Doctor P. Tornvall (Stockholm, SE)

Artificial intelligence-driven ECG biomarkers for accurate screening of large pericardial effusion

Speaker: Assistant Professor M. SOH (Suwon, KR)

AI-driven dual-ECG analysis for non-invasive monitoring of heart failure status changes

Speaker: Doctor Y. Nishihara (Kobe, JP)

Assessing the external performance of AI-ECG for left ventricular systolic dysfunction: a review and multinational head-to-head comparison

Speaker: Mr P. Croon (Amsterdam, NL)

Access the full session

Artificial intelligence in cardiology: transforming ECG analysis for precision care

Speakers: Miss C. Buck, Doctor A. Estrada-Magana, Doctor H. Hakansson, Doctor P. Tornvall, Assistant Professor M. SOH...

Access

About the event

ESC Congress 2025

29 August - 1 September 2025

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources

Explore sponsored resources

Explore sponsored resources