Frédéric Commandeur

Cedars-Sinai Medical Center — United States

Medicine · Health Sciences

21h-index2.6kcitations48works0.02yr avg
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Research Topics

Cardiac Imaging and Diagnostics(21), Cardiovascular Disease and Adiposity(16), Advanced X-ray and CT Imaging(9), Radiomics and Machine Learning in Medical Imaging(9), Medical Image Segmentation Techniques(8)

Publications48 total

Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective study
Cardiovascular Diabetology·2021· 61 citedOpen Access
Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective study
Atherosclerosis·2020· 60 citedOpen Access
Metabolic Syndrome, Fatty Liver, And Artificial Intelligence-based Epicardial Adipose Tissue Measures Predict Long-term Risk Of Cardiac Events
Journal of cardiovascular computed tomography·2020· 2 cited
Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT
European Heart Journal - Cardiovascular Imaging·2020· 63 cited
METABOLIC SYNDROME AND AUTOMATED EPICARDIAL ADIPOSE TISSUE MEASURES PREDICT LONG-TERM RISK OF CARDIAC EVENTS IN ASYMPTOMATIC SUBJECTS
Journal of the American College of Cardiology·2020
LONG-TERM PREDICTION OF CARDIAC EVENTS IN ASYMPTOMATIC SUBJECTS BY INTEGRATING NOVEL CIRCULATING AND IMAGING BIOMARKERS USING MACHINE LEARNING
Journal of the American College of Cardiology·2020
Deep Learning–Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects
Circulation Cardiovascular Imaging·2020· 151 citedOpen Access
Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study
Cardiovascular Research·2019· 138 citedOpen Access
Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study
Radiology Artificial Intelligence·2019· 137 citedOpen Access
Performance de l’analyse de texture en tomodensitométrie pour prédire la présence de graisse adhérente péri-rénale (« graisse toxique »)
Progrès en Urologie·2019
5963Automated quantification of epicardial adipose tissue from non-contrast CT on multi-center and multi-vendor data using deep learning
European Heart Journal·2019· 1 cited
29Prognostic safety of automatic cancellation of rest myocardial perfusion scan by machine learning: a report from multicenter REFINE SPECT registry of new generation SPECT
European Heart Journal·2019· 1 cited
P6151Fully automated epicardial adipose tissue volume and density measured from non-contrast CT predict major adverse cardiovascular events in asymptomatic subjects
European Heart Journal·2019
30Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study
European Heart Journal·2019· 26 cited
Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry
European Heart Journal - Cardiovascular Imaging·2019· 97 citedOpen Access
Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry
Journal of Nuclear Cardiology·2019· 25 citedOpen Access
Deep learning-based stenosis quantification from coronary CT angiography
2019· 49 citedOpen Access
PREDICTING MAJOR ADVERSE CARDIAC EVENTS WITH COX NEURAL NETWORKS: RESULTS FROM THE REFINE SPECT REGISTRY
Journal of the American College of Cardiology·2019· 2 cited
Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiography
European Heart Journal - Cardiovascular Imaging·2019· 226 citedOpen Access
Increased Pericoronary Adipose Tissue Attenuation Is Related To Progression Of Coronary Plaque Burden Quantified From Coronary Ct Angiography
Journal of cardiovascular computed tomography·2019· 2 cited
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Frequent Co-authors

Damini Dey(27), Daniel S. Berman(26), Piotr J. Slomka(26), Balaji Tamarappoo(21), Oscar Acosta(17), Markus Goeller(16), Sebastien Cadet(16), Xi Chen(16), R. de Crevoisier(16), Heidi Gransar(15), Stephan Achenbach(12), Aryabod Razipour(11), Robert J.H. Miller(11), Alan Rozanski(10), Romain Mathiéu(9), Stephanie Cantu(9), Julián Betancur(8), Nathan D. Wong(8), Priscilla McElhinney(8), Antoine Simon(8)