Back

ECGWiz: a unified and generalizable AI model for comprehensive ECG diagnosis

31 August 2024 (09:40 - 09:50)
Organised by: Logo
Congress Presentation Part of: Innovations in cardiac health prediction: integrating deep learning with multimodal data analysis Electrocardiogram (ECG) and Arrhythmia Analysis ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

Photo
Mr Ishan Vatsaraj

Baltimore (United States of America)

5 More presentations in this session

Presentation thumbnail
Mobile single-lead ECG atrial fibrillation prediction enhancement integrated by standard ECG algorithm with Deep learning model
Associate Professor K. Lee (Gwangju, KR)
Abstract Slides Video
Presentation thumbnail
Multi-modality deep learning prediction of heart age: insights from UK-Biobank.
Doctor G. Siontis (Bern, CH)
Abstract Slides Video
Presentation thumbnail
Detection and risk stratification of cardiac amyloidosis patients by integration of imaging and non-imaging data using a machine learning approach
Doctor C. Spielvogel (Vienna, AT)
Abstract Slides Video
Presentation thumbnail
Standardization of transthoracic impedance values for estimating heart failure and its utility
Doctor D. Nose (Fukuoka, JP)
Abstract Slides Video
Presentation thumbnail
Machine learning for prediction of incident heart failure and heart failure hospitalisation: multi-cohort development, validation and association with clinical phenotypes
Associate Professor Y. Nakao (Kyoto, JP)
Abstract Slides Video

Access the full session

Session thumbnail
Innovations in cardiac health prediction: integrating deep learning with multimodal data analysis
Video

The Event

Event poster

ESC Congress 2024

31 August 2024 09:40 CET
You may be interested in
thumbnail
Congress Session
Revolutionising cardiac diagnosis: exploring deep learning in electrocardiography and beyond
thumbnail
Congress Session
Innovations in cardiac health prediction: integrating deep learning with multimodal data analysis
thumbnail
Congress Session
Artificial intelligence guiding clinical diagnosis: from imaging to ECG

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources