Back

Deep and machine learning models to improve risk prediction of cardiovascular disease using data extraction from electronic health records.

31 August 2019 (00:00 - 00:00)
Organised by:
Congress Presentation Part of: Artificial intelligence M-health Big Data ESC Premium Access ESC Congress 2019

About the speaker

Photo
Assistant Professor Igor Korsakov

Almazov National Medical Research Centre, Saint Petersburg (Russian Federation)

5 More presentations in this session

Presentation thumbnail
Population-wide disease trajectories in ischaemic heart disease
Doctor A. Haue (Copenhagen, DK)
Abstract Slides
Presentation thumbnail
Machine learning versus classic electrocardiographic criteria for left ventricular hypertrophy in a young pre-participation cohort: results from the SAFE protocol study
Doctor G. Sng (Singapore, SG)
Abstract Slides
Presentation thumbnail
Artificial intelligence in echocardiography for standard clinical metrics
Mr W. Hewitt (Auckland, NZ)
Abstract Slides
Presentation thumbnail
A European randomised controlled trial for m-health guided cardiac rehabilitation in the elderly; results of the EU-CaRE RCT study
Doctor E. de Kluiver (Zwolle, NL)
Abstract Slides
Presentation thumbnail
Global telemedicine initiatives for combating ami
Doctor S. Mehta (Miami, US)
Abstract Slides

Access the full session

Session thumbnail
Artificial intelligence M-health

The Event

Event poster

ESC Congress 2019

31 August - 4 September 2019
You may be interested in
thumbnail
Congress Presentation
Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study
thumbnail
Congress Session
Evolutions in arrythmia and syncope management
thumbnail
Congress Presentation
Wearable technologies and digital biomarkers: validity and usability

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources