ESC Premium Access

A deep neural network predicts atrial fibrillation from normal ECGs recorded on a smartphone-enabled device

Topic: Big Data and Digital Twin

Congress Session

About the speaker

Mr Daniel Treiman

(United States of America)
0 follower

4 more presentations in this session

State of the Art - Machine learning: what it is and what it is not

Speaker: Associate Professor N. Duchateau (Villeurbanne, FR)

Thumbnail

A pattern-discovery-based outcome predictive tool integrated with clinical data repository: design and a case study on contrast related acute kidney injury

Speaker: Doctor Y. Li (Beijing, CN)

Thumbnail

Survival prediction in patients undergoing cardiac resynchronization therapy: a machine learning based risk stratification system

Speaker: Doctor M. Tokodi (Budapest, HU)

Thumbnail

A vision of the future for machine learning in cardiology

Speaker: Professor P. Sengupta (New Brunswick, US)

Thumbnail

Access the full session

Machine learning - State of the art

Speakers: Mr D. Treiman, Associate Professor N. Duchateau, Doctor Y. Li, Doctor M. Tokodi, Professor P. Sengupta
Thumbnail

About the event

Image

ESC CONGRESS 2019

31 August - 4 September 2019

Sessions Presentations

This platform is supported by

logo Novo Nordisk