Can artificial intelligence-derived coronary atherosclerotic characteristics using CCTA/CACS predict the future onset of atrial fibrillation?
Eur Heart J Imaging Methods Pract
.
2024 Sep 23;2(3):qyae098.
doi: 10.1093/ehjimp/qyae098.
eCollection 2024 Jul.
Authors
Andrew Chiou
1
,
Melody Hermel
2
,
Christina Rodriguez Ruiz
3
,
Alexander van Rosendael
4
,
Tim Burton
5
,
Francesca Calicchio
5
,
Samantha Bagsic
5
,
Eric Hu
5
,
Elizabeth Epstein
1
,
Casey Joye
6
,
Shawn Newlander
7
,
Michael Salerno
8
,
Sanjeev P Bhavnani
1
,
Austin Robinson
1
,
Jorge Gonzalez
9
,
George E Wesbey 3rd
9
Affiliations
1
Division of Cardiovascular Disease, Scripps Clinic, 9898 Genesee Avenue, AMP 400, La Jolla, CA 92037, USA.
2
Division of Cardiovascular Disease, Scripps Health & United Medical Doctors, La Jolla, CA, USA.
3
Department of Cardiology, Memorial Care Long Beach Medical Center, Long Beach, CA, USA.
4
Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
5
Department of Research & Development, Biostatistics, Scripps Health, La Jolla, CA, USA.
6
Department of Biological Science, Northwestern University, Evanston, IL, USA.
7
Department of Medical Physics, Scripps Health, La Jolla, CA, USA.
8
Department of Cardiovascular Disease, Stanford University, Palo Alto, CA, USA.
9
Division of Cardiovascular Disease & Radiology, Scripps Clinic, La Jolla, CA, USA.
PMID:
39391530
PMCID:
PMC11465160
DOI:
10.1093/ehjimp/qyae098
No abstract available
Grants and funding
UL1 TR002550/TR/NCATS NIH HHS/United States