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NPJ Digital Medicine
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May 1, 2023
Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging
Konrad Pieszko, Aakash D Shanbhag, Ananya Singh, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
May 5, 2022
Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging
Robert J H Miller, Keiichiro Kuronuma, Ananya Singh, et al.
JACC. Cardiovascular Imaging
|
August 24, 2020
Impact of Early Revascularization on Major Adverse Cardiovascular Events in Relation to Automatically Quantified Ischemia
Peyman N Azadani, Robert J H Miller, Tali Sharir, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
May 16, 2019
Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry
Lien-Hsin Hu, Tali Sharir, Robert J H Miller, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
April 17, 2023
Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging
Michelle C Williams, Bryan P Bednarski, Konrad Pieszko, 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 SPECT
Evann Eisenberg, Robert J H Miller, Lien-Hsin Hu, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
October 4, 2022
Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images
Robert J H Miller, Ananya Singh, Yuka Otaki, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
October 3, 2024
The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0)
Robert J H Miller, Mark Lemley, Aakash Shanbhag, et al.
Ebiomedicine
|
January 3, 2024
Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study
Robert J H Miller, Bryan P Bednarski, Konrad Pieszko, et al.
Circulation. Cardiovascular Imaging
|
July 20, 2021
Prognostic Value of Phase Analysis for Predicting Adverse Cardiac Events Beyond Conventional Single-Photon Emission Computed Tomography Variables: Results From the REFINE SPECT Registry
Keiichiro Kuronuma, Robert J H Miller, Yuka Otaki, et al.
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Search research articles
Search
Showing results (31-40 of 42) with videos related to
Sort By:
Page
of 5
NPJ Digital Medicine
|
May 1, 2023
Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging
Konrad Pieszko, Aakash D Shanbhag, Ananya Singh, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
May 5, 2022
Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging
Robert J H Miller, Keiichiro Kuronuma, Ananya Singh, et al.
JACC. Cardiovascular Imaging
|
August 24, 2020
Impact of Early Revascularization on Major Adverse Cardiovascular Events in Relation to Automatically Quantified Ischemia
Peyman N Azadani, Robert J H Miller, Tali Sharir, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
May 16, 2019
Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry
Lien-Hsin Hu, Tali Sharir, Robert J H Miller, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
April 17, 2023
Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging
Michelle C Williams, Bryan P Bednarski, Konrad Pieszko, 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 SPECT
Evann Eisenberg, Robert J H Miller, Lien-Hsin Hu, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
October 4, 2022
Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images
Robert J H Miller, Ananya Singh, Yuka Otaki, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
October 3, 2024
The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0)
Robert J H Miller, Mark Lemley, Aakash Shanbhag, et al.
Ebiomedicine
|
January 3, 2024
Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study
Robert J H Miller, Bryan P Bednarski, Konrad Pieszko, et al.
Circulation. Cardiovascular Imaging
|
July 20, 2021
Prognostic Value of Phase Analysis for Predicting Adverse Cardiac Events Beyond Conventional Single-Photon Emission Computed Tomography Variables: Results From the REFINE SPECT Registry
Keiichiro Kuronuma, Robert J H Miller, Yuka Otaki, et al.
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