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Diagnostic performance of non-invasive imaging for stable coronary artery disease: A meta-analysis

International journal of cardiology, 2020-02, Vol.300, p.276-281

2020

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Addressing bias: artificial intelligence in cardiovascular medicine

The Lancet. Digital health, 2020-12, Vol.2 (12), p.e635-e636

2020

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Interactions Among Vitamin D, Atrial Fibrillation, and the Renin-Angiotensin-Aldosterone System

The American journal of cardiology, 2018-09, Vol.122 (5), p.780-784

2018

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Prediction of myocardial blood flow under stress conditions by means of a computational model

European journal of nuclear medicine and molecular imaging, 2022-05, Vol.49 (6), p.1894-1905

2022

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Artificial Intelligence in Transcatheter Aortic Valve Replacement: Its Current Role and Ongoing Challenges

Diagnostics (Basel), 2024-01, Vol.14 (3), p.261

2024

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Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment

Journal of cardiovascular magnetic resonance, 2022-11, Vol.24 (1), p.62-62, Article 62

2022

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The Role of Cardiac Magnetic Resonance in Aortic Stenosis and Regurgitation

Journal of cardiovascular development and disease, 2022-04, Vol.9 (4), p.108

2022

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Transforming the Coronary Artery Disease Care Pathway Bridging Computational Fluid Dynamics to Coronary CTA

JACC. Cardiovascular imaging, 2022-06, Vol.15 (6), p.1059-1062

Rabbat, Mark G.

2022

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A Comprehensive Assessment of Cardiomyopathies through Cardiovascular Magnetic Resonance: Focus on the Pediatric Population

Diagnostics (Basel), 2022-04, Vol.12 (5), p.1022

2022

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Current and Future Applications of Artificial Intelligence in Coronary Artery Disease

Healthcare (Basel), 2022-01, Vol.10 (2), p.232

2022

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Interpreting results of coronary computed tomography angiography-derived fractional flow reserve in clinical practice

Journal of cardiovascular computed tomography, 2017-09, Vol.11 (5), p.383-388

2017

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Quantitative vs. qualitative evaluation of static stress computed tomography perfusion to detect haemodynamically significant coronary artery disease

European heart journal cardiovascular imaging, 2018-11, Vol.19 (11), p.1244-1252

2018

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Development and validation of a machine learned algorithm to IDENTIFY functionally significant coronary artery disease

Frontiers in cardiovascular medicine, 2022-09, Vol.9, p.956147-956147

2022

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Cardiovascular magnetic resonance of alcohol induced cardiomyopathy: Lost in the labyrinth of non-ischemic dilated cardiomyopathy

International journal of cardiology, 2021-06, Vol.332, p.133-134

2021

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Comprehensive Meta-Analysis on Drug-Eluting Stents versus Bare-Metal Stents during Extended Follow-up

The American journal of medicine, 2009-06, Vol.122 (6), p.581.e1-581.e10

2009

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1-Year Impact on Medical Practice and Clinical Outcomes of FFRCT: The ADVANCE Registry

JACC. Cardiovascular imaging, 2020-01, Vol.13 (1 Pt 1), p.97-105

2020

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Clinical Validation of a Machine-Learned, Point-of-Care System to IDENTIFY Functionally Significant Coronary Artery Disease

Diagnostics (Basel), 2024-05, Vol.14 (10), p.987

2024

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Understanding Coronary Physiology Through Dynamic CT Perfusion Imaging

JACC. Cardiovascular imaging, 2020-04, Vol.13 (4), p.977-979

2020

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SCCT Health Policy and Advocacy Efforts

Journal of cardiovascular computed tomography, 2024-09

2024

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Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA

Atherosclerosis, 2020-02, Vol.294, p.25-32

2020

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“Quadruple Rule-Out” With Computed Tomography in a COVID-19 Patient With Equivocal Acute Coronary Syndrome Presentation

JACC. Cardiovascular imaging, 2020-08, Vol.13 (8), p.1854-1856

2020

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Stress Computed Tomography Perfusion Versus Fractional Flow Reserve CT Derived in Suspected Coronary Artery Disease: The PERFECTION Study

JACC. Cardiovascular imaging, 2019-08, Vol.12 (8 Pt 1), p.1487-1497

2019

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The New Era of Computational Fluid Dynamics in CT Angiography: Far Beyond the FFR Number

JACC. Cardiovascular imaging, 2017-06, Vol.10 (6), p.674-676

2017

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Diagnostic performance of non-invasive imaging for stable coronary artery disease: A meta-analysis

Addressing bias: artificial intelligence in cardiovascular medicine

Interactions Among Vitamin D, Atrial Fibrillation, and the Renin-Angiotensin-Aldosterone System

Prediction of myocardial blood flow under stress conditions by means of a computational model

Artificial Intelligence in Transcatheter Aortic Valve Replacement: Its Current Role and Ongoing Challenges

Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment

The Role of Cardiac Magnetic Resonance in Aortic Stenosis and Regurgitation

Transforming the Coronary Artery Disease Care Pathway Bridging Computational Fluid Dynamics to Coronary CTA

A Comprehensive Assessment of Cardiomyopathies through Cardiovascular Magnetic Resonance: Focus on the Pediatric Population

Current and Future Applications of Artificial Intelligence in Coronary Artery Disease

Interpreting results of coronary computed tomography angiography-derived fractional flow reserve in clinical practice

Quantitative vs. qualitative evaluation of static stress computed tomography perfusion to detect haemodynamically significant coronary artery disease

Development and validation of a machine learned algorithm to IDENTIFY functionally significant coronary artery disease

Cardiovascular magnetic resonance of alcohol induced cardiomyopathy: Lost in the labyrinth of non-ischemic dilated cardiomyopathy

Comprehensive Meta-Analysis on Drug-Eluting Stents versus Bare-Metal Stents during Extended Follow-up

1-Year Impact on Medical Practice and Clinical Outcomes of FFRCT: The ADVANCE Registry

Clinical Validation of a Machine-Learned, Point-of-Care System to IDENTIFY Functionally Significant Coronary Artery Disease

Dynamic Stress Computed Tomography Perfusion With a Whole-Heart Coverage Scanner in Addition to Coronary Computed Tomography Angiography and Fractional Flow Reserve Computed Tomography Derived

Understanding Coronary Physiology Through Dynamic CT Perfusion Imaging

SCCT Health Policy and Advocacy Efforts

Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA

“Quadruple Rule-Out” With Computed Tomography in a COVID-19 Patient With Equivocal Acute Coronary Syndrome Presentation

Stress Computed Tomography Perfusion Versus Fractional Flow Reserve CT Derived in Suspected Coronary Artery Disease: The PERFECTION Study

Incremental Diagnostic Value of Stress Computed Tomography Myocardial Perfusion With Whole-Heart Coverage CT Scanner in Intermediate- to High-Risk Symptomatic Patients Suspected of Coronary Artery Disease

The New Era of Computational Fluid Dynamics in CT Angiography: Far Beyond the FFR Number

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