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

Session: Machine learning - State of the art
Topic: Big Data and Digital Twin
Speaker: Mr D. Treiman (US)
Event: ESC Congress 2019

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Mr Daniel Treiman

(United States of America)
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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)

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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)

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

Speaker: Doctor M. Tokodi (Budapest, HU)

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A vision of the future for machine learning in cardiology

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

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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
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ESC Congress 2019

31 August - 4 September 2019

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