Back

Improving the value of clinical variables in the assessment of cardiovascular risk using Artificial Neural Networks

27 August 2017 (10:05 - 10:55)
Organised by:
Congress Presentation Part of: Cardiovascular risk prediction models: for improvement? Cardiovascular risk ESC Premium Access ESC Congress 2017

About the speaker

Photo
Doctor Luis Eduardo Juarez-Orozco

University Medical Center Utrecht, Utrecht (Netherlands (The))

6 More presentations in this session

Presentation thumbnail
Incorporation of hospital outcomes into the GRACE Score improves its long-term prognostic value in acute coronary syndromes: The GRACE-Dynamic Score
Miss Y. Falcon Lacerda (Salvador, BR)
Abstract Slides
Presentation thumbnail
Serum hyperuricemia determination improves risk prediction of GRACE score in people with acute coronary syndrome.
Mrs A. Lopez Pineda (San Juan, ES)
Abstract Slides
Presentation thumbnail
Creating a prediction model to identify patients at high risk of undetected non-valvular atrial fibrillation
Professor M. Haim (Beer Sheva, IL)
Abstract Slides
Presentation thumbnail
Adding risk factors profile to pain characteristics does not increase the predictive power for coronary artery disease in chest pain patients
Doctor S. Thiru (Leeds, GB)
Abstract Slides
Presentation thumbnail
Glycemic variability, but not Hb1Ac, is associated with high SYNTAX scores at the acute phase of myocardial infarction in diabetic patients treated with insulin infusion
Doctor M. Benalia (Dijon, FR)
Abstract Slides

Access the full session

Session thumbnail
Cardiovascular risk prediction models: for improvement?

The Event

Event poster

ESC Congress 2017

27 August 2017 10:05 CET

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources