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Integrative machine learning model for predicting patient-oriented composite endpoints in acute myocardial infarction: a neuroendocrine biomarker approach

31 August 2024 (10:00 - 10:50)
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Congress Presentation Part of: Advancing cardiac care in acute coronary syndromes: from genetics to social determinants Epidemiology, Prognosis, Outcome ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Doctor Ali Aldujeli

Bon Secours Hospital Limerick, Co. Limerick (Ireland)

8 More presentations in this session

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Symptoms and ASCVD score fail to identify majority of the patients at risk of first myocardial infarction
Doctor A. Mueller (New York, US)
Abstract Slides
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Corrected timi frame count : time to replace the TIMI flow?
Mr S. Rifqi (Semarang, ID)
Abstract Slides
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Expression of cardiomyopathy-related genes in mononuclear blood cells predicts all-cause mortality in patients presenting with acute versus chronic coronary syndrome requiring revascularisation
Doctor A. Teren (Bielefeld, DE)
Abstract Slides Video
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Undiagnosed Diabetes Mellitus is an important risk factor in secondary prevention after an acute coronary syndrome and warrants active screening
Ms E. Woelders (Nijmegen, NL)
Abstract Slides Video
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Influence of social factors on prompt reperfusion in patients with ST-segment elevation myocardial infarction: results from the KRAMI multicenter registry
Doctor Z. Song (Busan, KR)
Abstract Slides Video

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Advancing cardiac care in acute coronary syndromes: from genetics to social determinants

The Event

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ESC Congress 2024

31 August 2024 10:00 CET
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ESC 365 is supported by

novartis Explore sponsored resources