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Automated Three-Dimensional Left Ventricular Volumes: Rise of the Machines?

Journal of the American Society of Echocardiography, 2019-09, Vol.32 (9), p.1116-1119

2019

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Commentary: Optimizing transfusion and hemostasis practices in cardiac surgery: Human versus machine or human and machine?

The Journal of thoracic and cardiovascular surgery, 2024-10, Vol.168 (4), p.1130-1131

2024

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Artificial intelligence for the echocardiographic assessment of valvular heart disease

Heart (British Cardiac Society), 2022-10, Vol.108 (20), p.1592-1599

2022

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Using Deep Convolutional Neural Networks to Automate Classification of Carotid Plaques from Ultrasound Imaging

JVS-vascular science, 2022, Vol.3, p.405-405

2022

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Four-Dimensional Echocardiography: Getting to the Root of the Matter

The Annals of thoracic surgery, 2021-10, Vol.112 (4), p.1324-1325

2021

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Mixed aortic stenosis and regurgitation: a clinical conundrum

Heart (British Cardiac Society), 2023-02, Vol.109 (4), p.264-275

2023

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Risk Assessment in Secondary Mitral Regurgitation

JACC. Advances (Online), 2022-08, Vol.1 (3), p.100074, Article 100074

2022

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Risk Assessment in Secondary Mitral Regurgitation: A Step Toward Clarity?

JACC. Advances (Online), 2022-08, Vol.1 (3), p.100074

2022

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The cardiac surgeon's guide to artificial intelligence

Current opinion in cardiology, 2021-09, Vol.36 (5), p.637-643

2021

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Machine learning as a new frontier in mitral valve surgical strategy

Journal of cardiac surgery, 2022-01, Vol.37 (1), p.84-87

2022

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Becoming proactive, not reactive: the cardiothoracic surgery job market in the coronavirus disease 2019 (COVID-19), era

Journal of thoracic disease, 2023-01, Vol.15 (1), p.5-9

2023

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Rapid deployment valves: Another tool in the toolbox

Journal of cardiac surgery, 2021-08, Vol.36 (8), p.2834-2835

2021

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Overcoming the Disparity in Mitral Valve Repair: A Sex-based Analysis of Long-term Outcomes

The Annals of thoracic surgery, 2024-08

2024

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Machine learning and decision making in aortic arch repair

The Journal of thoracic and cardiovascular surgery, 2023-11

2023

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Machine learning and readmission: Do we need new methods to solve old problems?

The Journal of thoracic and cardiovascular surgery, 2022-01, Vol.163 (1), p.e101-e102

2022

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Multiple Arterial Grafting Is Associated With Better Outcomes for Coronary Artery Bypass Grafting Patients

Circulation (New York, N.Y.), 2018-11, Vol.138 (19), p.2081-2090

2018

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Automated and Interpretable Deep Learning For Carotid Plaque Analysis Using Ultrasound

Journal of vascular surgery, 2023-10, Vol.78 (4), p.e82-e83

2023

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Systematic review and meta-analysis of chordal replacement versus leaflet resection for posterior mitral leaflet prolapse

The Journal of thoracic and cardiovascular surgery, 2018-01, Vol.155 (1), p.120-128.e10

2018

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Phenotypic Heterogeneity in Mixed Aortic Valve Disease Patients Using Machine Learning

Nedadur, Rashmi

2022

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Infected Pseudoaneurysm of an Outflow Graft After Left Ventricular Assist Device Insertion

Canadian journal of cardiology, 2024-07, Vol.40 (7), p.1352-1354

2024

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Abstract 13601: Distinct Proteomic Profiles in Human Thoracic Aortic Aneurysm by Segment May Drive Prognostic Differences: Conventional & Machine Learning Analysis

Circulation (New York, N.Y.), 2023-11, Vol.148 (Suppl_1)

2023

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Abstract 347: Using Deep Convolutional Neural Networks To Automate Classification Of Carotid Plaques From Ultrasound Imaging

Arteriosclerosis, thrombosis, and vascular biology, 2022-05, Vol.42 (Suppl_1)

2022

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Commentary: When starting a MICS program, Don't assume excellence: Prove it

Journal of cardiac surgery, 2021-03, Vol.36 (3), p.998-999

2021

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Rigid Plate Fixation Versus Wire Cerclage for Sternotomy After Cardiac Surgery: A Meta-Analysis

The Annals of thoracic surgery, 2018-07, Vol.106 (1), p.298-304

2018

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A MACHINE LEARNING MODEL FOR CHARACTERIZATION OF MIXED AORTIC VALVE DISEASE PATIENTS

Journal of the American College of Cardiology, 2021-05, Vol.77 (18), p.1694-1694

2021

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Automated Three-Dimensional Left Ventricular Volumes: Rise of the Machines?

Commentary: Optimizing transfusion and hemostasis practices in cardiac surgery: Human versus machine or human and machine?

Artificial intelligence for the echocardiographic assessment of valvular heart disease

Using Deep Convolutional Neural Networks to Automate Classification of Carotid Plaques from Ultrasound Imaging

Four-Dimensional Echocardiography: Getting to the Root of the Matter

Mixed aortic stenosis and regurgitation: a clinical conundrum

Risk Assessment in Secondary Mitral Regurgitation

Risk Assessment in Secondary Mitral Regurgitation: A Step Toward Clarity?

The cardiac surgeon's guide to artificial intelligence

Machine learning as a new frontier in mitral valve surgical strategy

Becoming proactive, not reactive: the cardiothoracic surgery job market in the coronavirus disease 2019 (COVID-19), era

Rapid deployment valves: Another tool in the toolbox

Overcoming the Disparity in Mitral Valve Repair: A Sex-based Analysis of Long-term Outcomes

Machine learning and decision making in aortic arch repair

Machine learning and readmission: Do we need new methods to solve old problems?

Multiple Arterial Grafting Is Associated With Better Outcomes for Coronary Artery Bypass Grafting Patients

Automated and Interpretable Deep Learning For Carotid Plaque Analysis Using Ultrasound

Systematic review and meta-analysis of chordal replacement versus leaflet resection for posterior mitral leaflet prolapse

Phenotypic Heterogeneity in Mixed Aortic Valve Disease Patients Using Machine Learning

Infected Pseudoaneurysm of an Outflow Graft After Left Ventricular Assist Device Insertion

Abstract 13601: Distinct Proteomic Profiles in Human Thoracic Aortic Aneurysm by Segment May Drive Prognostic Differences: Conventional & Machine Learning Analysis

Abstract 347: Using Deep Convolutional Neural Networks To Automate Classification Of Carotid Plaques From Ultrasound Imaging

Commentary: When starting a MICS program, Don't assume excellence: Prove it

Rigid Plate Fixation Versus Wire Cerclage for Sternotomy After Cardiac Surgery: A Meta-Analysis

A MACHINE LEARNING MODEL FOR CHARACTERIZATION OF MIXED AORTIC VALVE DISEASE PATIENTS

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