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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

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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

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