PuSH - Publication Server of Helmholtz Zentrum München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Bartelt, A. ; Leipsic, J.* ; Weber, C.*

The new age of radiomic risk profiling: perivascular fat at the heart of the matter.

Eur. Heart J. 40, 3544-3546 (2019)
Publ. Version/Full Text DOI PMC
Closed
Open Access Green as soon as Postprint is submitted to ZB.
This editorial refers to 'A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography'(dagger), by E.K. Oikonomou et al., on page 3529.
Web of Science
Times Cited
Scopus
Cited By
Altmetric
1
4
Tags
Annotations
Special Publikation
Hide on homepage

Edit extra information
Edit own tags
Private
Edit own annotation
Private
Hide on publication lists
on hompage
Mark as special
publikation
Publication type Article: Journal article
Document type Editorial
Language english
Publication Year 2019
HGF-reported in Year 2019
ISSN (print) / ISBN 0195-668X
e-ISSN 1522-9645
Journal European Heart Journal
Quellenangaben Volume: 40, Issue: 43, Pages: 3544-3546 Article Number: , Supplement: ,
Publisher Oxford University Press
Publishing Place Great Clarendon St, Oxford Ox2 6dp, England
Reviewing status Peer reviewed
Institute(s) Institute of Diabetes and Cancer (IDC)
POF-Topic(s) 90000 - German Center for Diabetes Research
Research field(s) Helmholtz Diabetes Center
PSP Element(s) G-501900-250
DOI 10.1093/eurheartj/ehz717
WOS ID WOS:000501743300010
Scopus ID 85075095243
PubMed ID 31605139
Erfassungsdatum 2019-10-16
[➜Report correction]