ESC 365 - A vision of the future for machine learning in cardiology

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A vision of the future for machine learning in cardiology

Session: Machine learning - State of the art

Topic: Hospital Information Systems, Electronic Medical Records, Clinical Decision Support

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

Event: ESC Congress 2019

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About the speaker

Professor Partho P Sengupta

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

34 presentations

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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)

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

Speaker: Mr D. Treiman (US)

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)

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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Machine learning - State of the art

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

About the event

ESC Congress 2019

31 August - 4 September 2019

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