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Frederic Commandeur

Showing results (11-20 of 21) with videos related to

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Cardiovascular Research|December 20, 2019
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 studyFrederic Commandeur, Piotr J Slomka, Markus Goeller, et al.
Journal of Cardiovascular Computed Tomography|December 14, 2017
Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjectsMarkus Goeller, Stephan Achenbach, Mohamed Marwan, et al.
Circulation. Cardiovascular Imaging|February 18, 2020
Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic SubjectsEvann Eisenberg, Priscilla A McElhinney, Frederic Commandeur, et al.
Cardiovascular Diabetology|January 30, 2021
Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective studyAndrew Lin, Nathan D Wong, Aryabod Razipour, et al.
European Heart Journal. Cardiovascular Imaging|February 22, 2019
Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiographyMarkus Goeller, Balaji K Tamarappoo, Alan C Kwan, et al.
Atherosclerosis|November 26, 2020
Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective studyBalaji K Tamarappoo, Andrew Lin, Frederic Commandeur, et al.
JACC. Cardiovascular Imaging|March 19, 2018
Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter StudyJulian Betancur, Frederic Commandeur, Mahsaw Motlagh, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|September 29, 2018
Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter StudyJulian Betancur, Lien-Hsin Hu, Frederic Commandeur, et al.
European Heart Journal. Cardiovascular Imaging|June 14, 2020
Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECTLien-Hsin Hu, Robert J H Miller, Tali Sharir, et al.
European Heart Journal. Cardiovascular Imaging|July 19, 2019
Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registryLien-Hsin Hu, Julian Betancur, Tali Sharir, et al.
Pageof 3

Showing results (11-20 of 21) with videos related to

Sort By:
Pageof 3
Cardiovascular Research|December 20, 2019
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 studyFrederic Commandeur, Piotr J Slomka, Markus Goeller, et al.
Journal of Cardiovascular Computed Tomography|December 14, 2017
Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjectsMarkus Goeller, Stephan Achenbach, Mohamed Marwan, et al.
Circulation. Cardiovascular Imaging|February 18, 2020
Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic SubjectsEvann Eisenberg, Priscilla A McElhinney, Frederic Commandeur, et al.
Cardiovascular Diabetology|January 30, 2021
Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective studyAndrew Lin, Nathan D Wong, Aryabod Razipour, et al.
European Heart Journal. Cardiovascular Imaging|February 22, 2019
Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiographyMarkus Goeller, Balaji K Tamarappoo, Alan C Kwan, et al.
Atherosclerosis|November 26, 2020
Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective studyBalaji K Tamarappoo, Andrew Lin, Frederic Commandeur, et al.
JACC. Cardiovascular Imaging|March 19, 2018
Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter StudyJulian Betancur, Frederic Commandeur, Mahsaw Motlagh, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|September 29, 2018
Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter StudyJulian Betancur, Lien-Hsin Hu, Frederic Commandeur, et al.
European Heart Journal. Cardiovascular Imaging|June 14, 2020
Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECTLien-Hsin Hu, Robert J H Miller, Tali Sharir, et al.
European Heart Journal. Cardiovascular Imaging|July 19, 2019
Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registryLien-Hsin Hu, Julian Betancur, Tali Sharir, et al.
Pageof 3