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Presentation TCT 2025

TCT 965: Can Machine Learning Aid the Evaluation of the Risks of Bleeding vs Thrombotic Events in Patients at High Bleeding Risk After PCI?

Presenter: Hao-Yu Wang

October 28, 2025

Presentation TCT 2025

TCT 1015: External Validation of the xDAPT Machine Learning Model for Ischemic and Bleeding Risk After Percutaneous Coronary Intervention

Presenter: Davide Cao

October 28, 2025

Presentation TCT 2025

TCT 916: Machine Learning to Predict Neurological Outcome after Out-of-hospital Cardiac Arrest

Presenter: Johannes Michael Altstidl

October 27, 2025

Presentation TCT 2025

TCT 476: Synergistic Impact of Insulin Resistance and Hepatic Fibrosis on Cardiovascular Events in Patients with Coronary Artery Disease: A Machine Learning Subtyping and Interaction Analysis

Presenter: Zhihao Zheng

October 27, 2025

Presentation TCT 2025

TCT 433: Can Major Cardiovascular Adverse Events (MACE) be Predicted? A Systematic Review and Meta-Analysis Exploring the Use of Machine Learning (ML) with Coronary Computed Tomography Angiography (CCTA)

Presenter: Saif Syed

October 27, 2025

Presentation TCT 2025

Featured Innovation: Automated Diagnosis and Classification of Aortic Stenosis from A Single Echocardiographic View: A Novel Machine Learning Approach

Presenter: Mayooran Namasivayam

October 26, 2025

Presentation TCT 2025

TCT 149: Prediction of Percutaneous Coronary Intervention Success in Moderate-to-severe Coronary Artery Calcification Patients Using Machine Learning Based on Coronary Angiography

Presenter: Zixiang Ye

October 26, 2025

Presentation TCT 2025

TCT 1059: Prediction of Patient Radiation Dose During Chronic Total Occlusion Percutaneous Coronary Intervention: A Machine Learning Augmented Analysis

Presenter: Pedro Carvalho

October 26, 2025

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 264: Improving Risk Stratification of SCAI Stages of Cardiogenic Shock With Machine Learning-Based Phenotyping

Presenter: Elric Zweck

October 29, 2024

Presentation TCT 2024

TCT 192: Beta-Blocker Efficacy in Acute Myocardial Infarction: A Machine Learning Approach Using the KAMIR-NIH Dataset

Presenter: Woo Jin Ahn

October 27, 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 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 TCT 2023

TCT 197: Machine Learning Model for Predicting Mortality in Acute Myocardial Infarction Patients managed with or without Beta-Blocker

Presenter: Seung-Woon Rha

October 26, 2023

Presentation TCT 2023

TCT 607: Machine Learning for Predicting Major Adverse Cardiac Events in Percutaneous Coronary Intervention of Coronary Artery Chronic Total Occlusion

Presenter: Judit Karacsonyi

October 25, 2023

Presentation TCT 2023

TCT 284: Do the Novel Pulmonary Risk Factors Identified by the Machine Learning Have an Impact on Outcomes of Revascularisation in Complex Coronary Artery Disease?

Presenter: SHIGETAKA KAGEYAMA

October 25, 2023

Presentation TCT 2023

TCT 715: Laminar Flow Predicted Correctly No Progression in Severity of Moderate Stenotic Lesion: a Dynamic Angiographic and Machine Learning Analysis

Presenter: Duc Nguyen

October 24, 2023

Presentation TCT 2023

Predicting Ischemic and Bleeding Risk in Patients after PCI on DAPT: An Individualized Patient Centered Machine Learning Model

Presenter: Roxana Mehran

October 24, 2023

Presentation TCT 2023

Counterpoint: AI and Machine Learning Have Significant Limitations – A Word of Caution

Presenter: Mamas Mamas

October 23, 2023

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TCT 965: Can Machine Learning Aid the Evaluation of the Risks of Bleeding vs Thrombotic Events in Patients at High Bleeding Risk After PCI?

TCT 1015: External Validation of the xDAPT Machine Learning Model for Ischemic and Bleeding Risk After Percutaneous Coronary Intervention

TCT 916: Machine Learning to Predict Neurological Outcome after Out-of-hospital Cardiac Arrest

TCT 476: Synergistic Impact of Insulin Resistance and Hepatic Fibrosis on Cardiovascular Events in Patients with Coronary Artery Disease: A Machine Learning Subtyping and Interaction Analysis

TCT 433: Can Major Cardiovascular Adverse Events (MACE) be Predicted? A Systematic Review and Meta-Analysis Exploring the Use of Machine Learning (ML) with Coronary Computed Tomography Angiography (CCTA)

Featured Innovation: Automated Diagnosis and Classification of Aortic Stenosis from A Single Echocardiographic View: A Novel Machine Learning Approach

TCT 149: Prediction of Percutaneous Coronary Intervention Success in Moderate-to-severe Coronary Artery Calcification Patients Using Machine Learning Based on Coronary Angiography

TCT 1059: Prediction of Patient Radiation Dose During Chronic Total Occlusion Percutaneous Coronary Intervention: A Machine Learning Augmented Analysis

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

TCT 264: Improving Risk Stratification of SCAI Stages of Cardiogenic Shock With Machine Learning-Based Phenotyping

TCT 192: Beta-Blocker Efficacy in Acute Myocardial Infarction: A Machine Learning Approach Using the KAMIR-NIH Dataset

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

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

TCT 197: Machine Learning Model for Predicting Mortality in Acute Myocardial Infarction Patients managed with or without Beta-Blocker

TCT 607: Machine Learning for Predicting Major Adverse Cardiac Events in Percutaneous Coronary Intervention of Coronary Artery Chronic Total Occlusion

TCT 284: Do the Novel Pulmonary Risk Factors Identified by the Machine Learning Have an Impact on Outcomes of Revascularisation in Complex Coronary Artery Disease?

TCT 715: Laminar Flow Predicted Correctly No Progression in Severity of Moderate Stenotic Lesion: a Dynamic Angiographic and Machine Learning Analysis

Predicting Ischemic and Bleeding Risk in Patients after PCI on DAPT: An Individualized Patient Centered Machine Learning Model

Counterpoint: AI and Machine Learning Have Significant Limitations – A Word of Caution

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