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Document type:
Zeitschriftenaufsatz
Author(s):
Güldener, Ulrich ; Kessler, Thorsten ; von Scheidt, Moritz ; Hawe, Johann S. ; Gerhard, Beatrix ; Maier, Dieter ; Lachmann, Mark ; Laugwitz, Karl-Ludwig ; Cassese, Salvatore ; Schömig, Albert W. ; Kastrati, Adnan ; Schunkert, Heribert
Title:
Machine Learning Identifies New Predictors on Restenosis Risk after Coronary Artery Stenting in 10,004 Patients with Surveillance Angiography
Keywords:
Article ; artificial intelligence ; coronary artery disease ; machine learning ; percutaneous coronary intervention ; prediction ; restenosis
Journal title:
Journal of Clinical Medicine
Year:
2023
Journal volume:
12
Journal issue:
8
Fulltext / DOI:
doi:10.3390/jcm12082941
Publisher:
MDPI
E-ISSN:
2077-0383
Date of publication:
18.04.2023
CC license:
by, https://creativecommons.org/licenses/by/4.0
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