ESC 365 - Comparison of the discriminative ability of artificial neural networks and GRACE score for prediction of mortality in acute coronary syndromes.

ESC2025 Premium Access

Comparison of the discriminative ability of artificial neural networks and GRACE score for prediction of mortality in acute coronary syndromes.

Session: Artificial intelligence in acute coronary syndromes

Topic: Epidemiology, Prognosis, Outcome

Speaker: Doctor J. Struzka (Buenos Aires, AR)

Event: ESC Congress 2025

Congress Presentation

Add to my library

About the speaker

Doctor J Struzka

Hospital Aleman, Buenos Aires (Argentina)

0 follower

4 more presentations in this session

Leveraging machine learning for rapid rule-out of acute coronary syndrome

Speaker: Mr D. Sesia (ZM) Doctor A. Kaura (London, GB)

Training and validation of an ECG-based deep-learning model for the early diagnosis of acute myocardial infarction

Speaker: Doctor T. Zimmermann (Basel, CH)

Deep-Learning based approach to ED chest pain risk stratification by ECG

Speaker: Doctor S. Parsa (Stanford, US)

External validation of the ECG-SMART model: a machine learning algorithm for ECG diagnosis of occlusion myocardial infarction

Speaker: Doctor P. Lopez Ayala (Basel, CH)

Access the full session

Artificial intelligence in acute coronary syndromes

Speakers: Doctor J. Struzka, Mr D. Sesia, Doctor A. Kaura, Doctor T. Zimmermann, Doctor S. Parsa...

About the event

ESC Congress 2025

29 August - 1 September 2025

Sessions Presentations

Congress

ESC 365 is supported by

bristol-myers-squibb

Explore sponsored resources

novartis

Explore sponsored resources

novo-nordisk

Explore sponsored resources