Back

Electrocardiographic age as a predictor of cardiovascular events in Brazilian adults: from the ELSA-Brasil study

31 August 2025 (08:15 - 09:00)
Organised by: Logo
Congress Presentation Part of: Risk stratification models: leveraging digital health for better outcomes Deep Learning ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

Photo
Mrs Ana Luiza Ciminelli

Hospital das Clinicas da UFMG, Belo Horizonte (Brazil)

7 More presentations in this session

Presentation thumbnail
Personalized approach to cardiovascular risk stratification: a randomized controlled trial evaluating the effectiveness of an AI-developed diet versus a standard mediterranean diet
Mr B. Rozibaev (Tashkent, UZ)
Abstract Slides Video
Presentation thumbnail
Comparing machine learning models with established risk scores in predicting bleeding and ischaemic stroke in patients with atrial fibrillation undergoing transcatheter aortic valve implantation
Doctor G. Dangas (New York, US)
Abstract Slides
Presentation thumbnail
Prediction of atrial fibrillation from the electrocardiogram in the community using deep learning
Doctor L. Brant (Belo Horizonte, BR)
Abstract Slides Video
Presentation thumbnail
Leveraging AI and clinical guidelines to identify undiagnosed and under-treated CKD patients for treatment optimisation
Ms A. Veldman (The Hague, NL)
Abstract Slides Video
Presentation thumbnail
Quick and easy multi-pathology cardiovascular disease detection with an artificial intelligence-enabled stethoscope: multi-centre prospective validation study in secondary care
Doctor P. Bachtiger (London, GB)
Abstract Slides Video

Access the full session

Session thumbnail
Risk stratification models: leveraging digital health for better outcomes

The Event

Event poster

ESC Congress 2025

31 August 2025 08:15 CET
You may be interested in
thumbnail
Congress Presentation
The association between cardiovascular health and physiologic age as determined by artificial intelligence-enabled electrocardiography
thumbnail
Congress Presentation
Prognostic assessment based on the trajectory of artificial intelligence-enabled electrocardiograms for age estimation
thumbnail
Congress Presentation
AI-ECG-derived biological age as a predictor of mortality in cardiovascular and acute care patients

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources