Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study

Commandeur FC, Slomka PJ, Göller M, Chen X, Cadet S, Razipour A, Gransar H, Cantu S, Miller R, Rozanski A, Achenbach S, Tamarappoo B, Berman D, Dey D (2019)

Publication Type: Conference contribution

Publication year: 2019

Journal

European Heart Journal Oxford University Press

Publisher: OXFORD UNIV PRESS

City/Town: OXFORD

Pages Range: 4-4

Conference Proceedings Title: EUROPEAN HEART JOURNAL

Event location: Paris FR

DOI: 10.1093/cvr/cvz321

Authors with CRIS profile

Markus Göller Department of Medicine 2 – Cardiology and Angiology Stephan Achenbach Lehrstuhl für Innere Medizin II

Involved external institutions

Cedars-Sinai Medical Center US United States (USA) (US)

How to cite

APA:

Commandeur, F.C., Slomka, P.J., Göller, M., Chen, X., Cadet, S., Razipour, A.,... Dey, D. (2019). Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study. In EUROPEAN HEART JOURNAL (pp. 4-4). Paris, FR: OXFORD: OXFORD UNIV PRESS.

MLA:

Commandeur, F. C., et al. "Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study." Proceedings of the ESC Congress / World Congress of Cardiology, Paris OXFORD: OXFORD UNIV PRESS, 2019. 4-4.

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