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Machine learning in critical care: the role of diabetes and age in acute coronary syndromes

Session: Poster Session 7 - Acute Coronary Syndromes - Risk stratification, machine learning
Topic: Epidemiology, Prognosis, Outcome
Speaker: Doctor E. Cenko (Bologna, IT)
Event: ESC Congress 2019

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Doctor Edina Cenko

University of Bologna, Bologna (Italy)
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Increasing the accuracy of a machine learning algorithm for stemi diagnosis by incorporating demographic variables

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The continued proficiency of artificial intelligence for interpreting ekg: single lead ekg for stemi culprit lesion localization

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Can machine learning help us improve risk stratification of diabetic patients with acute coronary syndromes? The answer will blow your mind

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Can cardiologists rely on artificial intelligence to identify the culprit vessel in stemi?

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Physician vs machine: an innovative st-elevation myocardial infarction pathway through artificial intelligence

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Access the full session

Poster Session 7 - Acute Coronary Syndromes - Risk stratification, machine learning

Speakers: Doctor E. Cenko, Doctor A. Frauenfelder, Doctor S. Mehta, Doctor J. Milner, Doctor D. Vieira...
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ESC Congress 2019

31 August - 4 September 2019

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