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

26 August 2017 (00:00 - 00:00)
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Congress Presentation Part of: Cardiovascular risk prediction models: for improvement? Cardiovascular risk ESC Premium Access ESC Congress 2017

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Doctor Luis Eduardo Juarez-Orozco

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

6 More presentations in this session

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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)
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Serum hyperuricemia determination improves risk prediction of GRACE score in people with acute coronary syndrome.
Mrs A. Lopez Pineda (San Juan, ES)
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Creating a prediction model to identify patients at high risk of undetected non-valvular atrial fibrillation
Professor M. Haim (Beer Sheva, IL)
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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)
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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)
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Cardiovascular risk prediction models: for improvement?

The Event

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ESC Congress 2017

26 August - 30 August 2017

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources