Back

A vision of the future for machine learning in cardiology

31 August 2019 (00:00 - 00:00)
Organised by:
Congress Presentation Part of: Machine learning - State of the art m-Health & Mobile Apps ESC Premium Access ESC Congress 2019

About the speaker

Photo
Professor Partho P Sengupta

Robert Wood Johnson University Hospital, New Brunswick (United States of America)

4 More presentations in this session

Presentation thumbnail
State of the Art - Machine learning: what it is and what it is not
Associate Professor N. Duchateau (Villeurbanne, FR)
Slides Video
Presentation thumbnail
A deep neural network predicts atrial fibrillation from normal ECGs recorded on a smartphone-enabled device
Mr D. Treiman (US)
Abstract Slides Video
Presentation thumbnail
A pattern-discovery-based outcome predictive tool integrated with clinical data repository: design and a case study on contrast related acute kidney injury
Doctor Y. Li (Beijing, CN)
Abstract Slides Video
Presentation thumbnail
Survival prediction in patients undergoing cardiac resynchronization therapy: a machine learning based risk stratification system
Doctor M. Tokodi (Budapest, HU)
Abstract

Access the full session

Session thumbnail
Machine learning - State of the art

The Event

Event poster

ESC Congress 2019

31 August - 4 September 2019
You may be interested in
thumbnail
Congress Session
How to implement a successful telemedicine program in heart failure
thumbnail
Congress Presentation
Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study
thumbnail
Congress Presentation
Let’s go digital: implementing cardiac rehabilitation - discussion

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources