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M Timothy Hauser

Showing results (1-10 of 9) with videos related to

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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.
European Journal of Nuclear Medicine and Molecular Imaging|October 27, 2025
Risk stratification with pre-operative myocardial perfusion imagingDayoung Kim, Valerie Builoff, Tali Sharir, et al.
The Canadian Journal of Cardiology|May 14, 2025
Reassessing Cardiovascular Risk in Patients With Peripheral Artery Disease Undergoing Myocardial Perfusion ImagingKaiming Wang, Tali Sharir, M Timothy Hauser, et al.
JACC. Advances|January 6, 2025
The Relationship Between Quantitative Ischemia, Early Revascularization, and Major Adverse Cardiovascular Events: A Multicenter StudyRobert Jh Miller, Bryan Bednarski, Yujie Cui, et al.
NPJ Digital Medicine|May 1, 2023
Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imagingKonrad Pieszko, Aakash D Shanbhag, Ananya Singh, 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 imagingMichelle C Williams, Bryan P Bednarski, Konrad Pieszko, 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 studyRobert J H Miller, Bryan P Bednarski, Konrad Pieszko, et al.
Medrxiv : the Preprint Server for Health Sciences|June 30, 2025
AI-based identification of patients who benefit from revascularization: a multicenter studyWenhao Zhang, Robert Jh Miller, Krishna Patel, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
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.
European Journal of Nuclear Medicine and Molecular Imaging|October 27, 2025
Risk stratification with pre-operative myocardial perfusion imagingDayoung Kim, Valerie Builoff, Tali Sharir, et al.
The Canadian Journal of Cardiology|May 14, 2025
Reassessing Cardiovascular Risk in Patients With Peripheral Artery Disease Undergoing Myocardial Perfusion ImagingKaiming Wang, Tali Sharir, M Timothy Hauser, et al.
JACC. Advances|January 6, 2025
The Relationship Between Quantitative Ischemia, Early Revascularization, and Major Adverse Cardiovascular Events: A Multicenter StudyRobert Jh Miller, Bryan Bednarski, Yujie Cui, et al.
NPJ Digital Medicine|May 1, 2023
Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imagingKonrad Pieszko, Aakash D Shanbhag, Ananya Singh, 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 imagingMichelle C Williams, Bryan P Bednarski, Konrad Pieszko, 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 studyRobert J H Miller, Bryan P Bednarski, Konrad Pieszko, et al.
Medrxiv : the Preprint Server for Health Sciences|June 30, 2025
AI-based identification of patients who benefit from revascularization: a multicenter studyWenhao Zhang, Robert Jh Miller, Krishna Patel, et al.
Pageof 1