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Jonathan B Moody

Showing results (41-50 of 46) with videos related to

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Cell Reports. Medicine|September 26, 2024
Development and validation of a machine learning model to predict myocardial blood flow and clinical outcomes from patients' electrocardiogramsFares Alahdab, Maliazurina Binti Saad, Ahmed Ibrahim Ahmed, et al.
NEJM AI|December 25, 2025
A foundation transformer model with self-supervised learning for ECG-based assessment of cardiac and coronary functionJonathan B Moody, Alexis Poitrasson-Rivière, Jennifer M Renaud, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|August 7, 2025
Comparison, Agreement, and Significance Cutoffs of <sup>18</sup>F-Flurpiridaz PET Myocardial Blood Flow Quantitation Methods and Software PackagesRené R Sevag Packard, Christopher Buckley, C David Cooke, et al.
European Journal of Nuclear Medicine and Molecular Imaging|October 8, 2023
Integrated myocardial flow reserve (iMFR) assessment: optimized PET blood flow quantification for diagnosis of coronary artery diseaseAlexis Poitrasson-Rivière, Jonathan B Moody, Jennifer M Renaud, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|April 30, 2020
Reproducible Quantification of Regional Sympathetic Denervation with [<sup>11</sup>C]meta-Hydroxyephedrine PET ImagingJean Z Wang, Jonathan B Moody, Nicole Kaps, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|August 23, 2024
How to differentiate obstructive from non-obstructive CAD with PET: Developments in high-resolution regional quantification of MBF and MFRJennifer M Renaud, Mouaz H Al-Mallah, Prem Soman, et al.
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Showing results (41-50 of 46) with videos related to

Sort By:
Pageof 5
You have reached the last page of results.This site can display upto 46 results.
Cell Reports. Medicine|September 26, 2024
Development and validation of a machine learning model to predict myocardial blood flow and clinical outcomes from patients' electrocardiogramsFares Alahdab, Maliazurina Binti Saad, Ahmed Ibrahim Ahmed, et al.
NEJM AI|December 25, 2025
A foundation transformer model with self-supervised learning for ECG-based assessment of cardiac and coronary functionJonathan B Moody, Alexis Poitrasson-Rivière, Jennifer M Renaud, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|August 7, 2025
Comparison, Agreement, and Significance Cutoffs of <sup>18</sup>F-Flurpiridaz PET Myocardial Blood Flow Quantitation Methods and Software PackagesRené R Sevag Packard, Christopher Buckley, C David Cooke, et al.
European Journal of Nuclear Medicine and Molecular Imaging|October 8, 2023
Integrated myocardial flow reserve (iMFR) assessment: optimized PET blood flow quantification for diagnosis of coronary artery diseaseAlexis Poitrasson-Rivière, Jonathan B Moody, Jennifer M Renaud, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|April 30, 2020
Reproducible Quantification of Regional Sympathetic Denervation with [<sup>11</sup>C]meta-Hydroxyephedrine PET ImagingJean Z Wang, Jonathan B Moody, Nicole Kaps, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|August 23, 2024
How to differentiate obstructive from non-obstructive CAD with PET: Developments in high-resolution regional quantification of MBF and MFRJennifer M Renaud, Mouaz H Al-Mallah, Prem Soman, et al.
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