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Presentation TCT 2024

Prediction of In-Hospital Mortality Following TAVI Using the FRANCE-TAVI Registry: A Machine Learning Approach

Presenter: Walid Ben-Ali

October 30, 2024

Presentation TCT 2024

TCT 210: Machine Learning Cluster Analysis Identifies Increased 12-Month Mortality Risk in Transcatheter Aortic Valve Replacement Recipients

Presenter: Thomas Meredith

October 27, 2024

Presentation NY Valves 2024

Aortic Shape Variants Defined by Unbiased Machine Learning Technique Predict Complications in Transcatheter Aortic Valve Replacement

Presenter: Michal Schafer

June 05, 2024

Presentation NY Valves 2024

Overview of the Role of Artificial Intelligence and Machine Learning for VHD Detection

Presenter: Timothy Joseph Poterucha

June 05, 2024

Presentation TCT 2023

TCT 775: A Machine Learning Based Model Predicts Death in Patients with Severe Asymptomatic Aortic Stenosis

Presenter: APURVA BHARUCHA

October 26, 2023

Presentation TCT 2023

TCT 753: Development of a Machine Learning Based Futility Risk Model to Predict One Year Mortality in Transcatheter Aortic Valve Replacement

Presenter: APURVA BHARUCHA

October 26, 2023

Presentation TVT 2019

Machine Learning-Based Prediction of Pacemaker Implantation After Transcatheter Aortic Valve Replacement

Presenter: Anvi Raina

June 14, 2019

Presentation TVT 2019

TAVR Safety in Cancer Including in Metastatic Disease: Propensity Score and Machine Learning Supported Multicenter Case-Control Study of Over 6 Million Hospitalizations

Presenter: Tariq Thannoun

June 14, 2019

Presentation TCT 2018

Patient-Specific Computer Simulation of TAVR in Bicuspid Aortic Valve Morphology

Presenter: Mayra Guerrero, James K. Min, Cameron Dowling

September 23, 2018

Presentation TCT 2018

Interactive Virtual Reality Imaging for Structural Heart Procedural Planning

Presenter: Mayra Guerrero, James K. Min, Saurabh Sanon

September 23, 2018

Presentation The Structural Heart Disease Summit 2018

The Underdiagnosis of Aortic Stenosis: A Novel Approach Using Machine Learning to Improve Acquisition and Interpretation of Echocardiograms

Presenter: Randolph P. Martin, Mark J. Russo

June 21, 2018

Presentation TCT 2017

Futuristic and Novel #2: Using Artificial Intelligence (Machine Learning) to Direct Acquisition and Interpretation of Echocardiograms Improving Access and Quality of Valve Disease Diagnosis

Presenter: Robert O. Bonow, Michael J. Mack, Randolph P. Martin

October 30, 2017

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Prediction of In-Hospital Mortality Following TAVI Using the FRANCE-TAVI Registry: A Machine Learning Approach

TCT 210: Machine Learning Cluster Analysis Identifies Increased 12-Month Mortality Risk in Transcatheter Aortic Valve Replacement Recipients

Aortic Shape Variants Defined by Unbiased Machine Learning Technique Predict Complications in Transcatheter Aortic Valve Replacement

Overview of the Role of Artificial Intelligence and Machine Learning for VHD Detection

TCT 775: A Machine Learning Based Model Predicts Death in Patients with Severe Asymptomatic Aortic Stenosis

TCT 753: Development of a Machine Learning Based Futility Risk Model to Predict One Year Mortality in Transcatheter Aortic Valve Replacement

Machine Learning-Based Prediction of Pacemaker Implantation After Transcatheter Aortic Valve Replacement

TAVR Safety in Cancer Including in Metastatic Disease: Propensity Score and Machine Learning Supported Multicenter Case-Control Study of Over 6 Million Hospitalizations

Patient-Specific Computer Simulation of TAVR in Bicuspid Aortic Valve Morphology

Interactive Virtual Reality Imaging for Structural Heart Procedural Planning

The Underdiagnosis of Aortic Stenosis: A Novel Approach Using Machine Learning to Improve Acquisition and Interpretation of Echocardiograms

Futuristic and Novel #2: Using Artificial Intelligence (Machine Learning) to Direct Acquisition and Interpretation of Echocardiograms Improving Access and Quality of Valve Disease Diagnosis

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