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Donghee Han

Showing results (131-140 of 166) with videos related to

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Diabetes Care|November 29, 2019
Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT RegistryDonghee Han, Alan Rozanski, Heidi Gransar, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|June 7, 2022
Machine learning to predict abnormal myocardial perfusion from pre-test featuresRobert J H Miller, M Timothy Hauser, Tali Sharir, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|January 16, 2023
Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trialKeiichiro Kuronuma, Pepijn A van Diemen, Donghee Han, et al.
Circulation. Cardiovascular Imaging|October 17, 2022
Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood FlowAndrew Lin, Pepijn A van Diemen, Manish Motwani, et al.
Atherosclerosis|June 3, 2018
Quantitative measurement of lipid rich plaque by coronary computed tomography angiography: A correlation of histology in sudden cardiac deathDonghee Han, Sho Torii, Kazuyuki Yahagi, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|November 10, 2021
Comparison of diabetes to other prognostic predictors among patients referred for cardiac stress testing: A contemporary analysis from the REFINE SPECT RegistryDonghee Han, Alan Rozanski, Heidi Gransar, et al.
JACC. Cardiovascular Imaging|October 15, 2019
Identification and Quantification of Cardiovascular Structures From CCTA: An End-to-End, Rapid, Pixel-Wise, Deep-Learning MethodLohendran Baskaran, Gabriel Maliakal, Subhi J Al'Aref, et al.
BMC Cardiovascular Disorders|October 8, 2016
Rationale and Design of the CREDENCE Trial: computed TomogRaphic evaluation of atherosclerotic DEtermiNants of myocardial IsChEmiaAsim Rizvi, Bríain Ó Hartaigh, Paul Knaapen, et al.
Journal of Cardiovascular Computed Tomography|November 14, 2022
Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortiumFay Y Lin, Benjamin P Goebel, Benjamin C Lee, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|July 6, 2021
Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECTEvann Eisenberg, Robert J H Miller, Lien-Hsin Hu, et al.
Pageof 17

Showing results (131-140 of 166) with videos related to

Sort By:
Pageof 17
Diabetes Care|November 29, 2019
Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT RegistryDonghee Han, Alan Rozanski, Heidi Gransar, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|June 7, 2022
Machine learning to predict abnormal myocardial perfusion from pre-test featuresRobert J H Miller, M Timothy Hauser, Tali Sharir, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|January 16, 2023
Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trialKeiichiro Kuronuma, Pepijn A van Diemen, Donghee Han, et al.
Circulation. Cardiovascular Imaging|October 17, 2022
Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood FlowAndrew Lin, Pepijn A van Diemen, Manish Motwani, et al.
Atherosclerosis|June 3, 2018
Quantitative measurement of lipid rich plaque by coronary computed tomography angiography: A correlation of histology in sudden cardiac deathDonghee Han, Sho Torii, Kazuyuki Yahagi, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|November 10, 2021
Comparison of diabetes to other prognostic predictors among patients referred for cardiac stress testing: A contemporary analysis from the REFINE SPECT RegistryDonghee Han, Alan Rozanski, Heidi Gransar, et al.
JACC. Cardiovascular Imaging|October 15, 2019
Identification and Quantification of Cardiovascular Structures From CCTA: An End-to-End, Rapid, Pixel-Wise, Deep-Learning MethodLohendran Baskaran, Gabriel Maliakal, Subhi J Al'Aref, et al.
BMC Cardiovascular Disorders|October 8, 2016
Rationale and Design of the CREDENCE Trial: computed TomogRaphic evaluation of atherosclerotic DEtermiNants of myocardial IsChEmiaAsim Rizvi, Bríain Ó Hartaigh, Paul Knaapen, et al.
Journal of Cardiovascular Computed Tomography|November 14, 2022
Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortiumFay Y Lin, Benjamin P Goebel, Benjamin C Lee, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|July 6, 2021
Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECTEvann Eisenberg, Robert J H Miller, Lien-Hsin Hu, et al.
Pageof 17