Invited Editorial - Marius Roman(CLEAN).pdf (574.77 kB)
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Are neural networks the ultimate risk prediction models in patients at high risk of acute myocardial infarction?

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journal contribution
posted on 10.03.2020, 14:10 by Marius Roman
Identifying and phenotyping patients at risk of developing major cardiovascular events is an ongoing research priority. With an abundance of variables and confounders, the current prediction tools based on linear multivariate regression models are becoming outpowered by the emerging machine learning algorithms. These algorithms have the potential to identify, with a higher prediction power healthy patients at risk, prompting preventive interventions, such as early screening imaging tools or medical therapy (e.g. antiplatelet therapy).

History

Citation

European Journal of Preventive Cardiology, 2020

Author affiliation

Department of Cardiovascular Sciences

Version

AM (Accepted Manuscript)

Published in

European Journal of Preventive Cardiology

Publisher

SAGE Publications

issn

2047-4873

eissn

2047-4881

Copyright date

2020

Available date

28/01/2020

Publisher version

https://journals.sagepub.com/doi/10.1177/2047487319890972

Spatial coverage

England

Language

eng