ESC 365 - Artificial intelligence algorithms for the recognition of Brugada type 1 pattern on standard 12-leads ECG

EHRA Premium Access

Artificial intelligence algorithms for the recognition of Brugada type 1 pattern on standard 12-leads ECG

Session: e-Cardiology award session

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Mr F. Vozzi (Pisa, IT)

Event: EHRA 2022

Congress Presentation

Add to my library

About the speaker

Mr Federico Vozzi

National Council of Research, Pisa (Italy)

0 follower

4 more presentations in this session

The impact of a structured polygraphy screening incorporated in a novel remote mobile health pathway on sleep apnoea prevalence in patients with atrial fibrillation

Speaker: Miss D. Verhaert (Nijmegen, NL)

Clinical validation of five direct-to-consumer smartwatches to detect atrial fibrillation in a real-world cohort of patients

Speaker: Doctor P. Badertscher (Basel, CH)

Classification of organised atrial arrythmias using explainable artificial intelligence

Speaker: Doctor A. Sau (London, GB)

Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals

Speaker: Doctor P. Pantelidis (Athens, GR)

Access the full session

e-Cardiology award session

Speakers: Mr F. Vozzi, Miss D. Verhaert, Doctor P. Badertscher, Doctor A. Sau, Doctor P. Pantelidis

About the event

EHRA 2022

3 April - 5 April 2022

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources

Explore sponsored resources