Deep convolutional neural networks to predict cardiovascular risk from computed tomography

Coronary artery calcium is an accurate predictor of cardiovascular events but this information is not routinely quantified. Here the authors show a robust and time-efficient deep learning system to automatically quantify coronary calcium on CT scans and predict cardiovascular events in a large, mult...

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Bibliographic Details
Main Authors: Roman Zeleznik, Borek Foldyna, Parastou Eslami, Jakob Weiss, Ivanov Alexander, Jana Taron, Chintan Parmar, Raza M. Alvi, Dahlia Banerji, Mio Uno, Yasuka Kikuchi, Julia Karady, Lili Zhang, Jan-Erik Scholtz, Thomas Mayrhofer, Asya Lyass, Taylor F. Mahoney, Joseph M. Massaro, Ramachandran S. Vasan, Pamela S. Douglas, Udo Hoffmann, Michael T. Lu, Hugo J. W. L. Aerts
Format: Article
Language:English
Published: Nature Publishing Group 2021-01-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-20966-2
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Summary:Coronary artery calcium is an accurate predictor of cardiovascular events but this information is not routinely quantified. Here the authors show a robust and time-efficient deep learning system to automatically quantify coronary calcium on CT scans and predict cardiovascular events in a large, multicentre study.
ISSN:2041-1723