Search - tctmd.com

Displaying 1 - 7 of 7

Sort: Relevancy | Date

Presentation THT 2026

Cutaneous device and machine learning could estimate pulmonary capillary wedge pressure in patients with heart failure

Presenter: Remi Sabatier

March 04, 2026

Presentation THT 2026

UltraSight PVAD IQ Machine Learning Algorithm Accurately Identifies Impella Micro-axial Flow Pump Depth Across the Aortic Valve on Ultrasound Imaging: An Early Clinical Feasibility Study

Presenter: Luca Baldetti

March 03, 2026

Presentation THT 2026

Beyond Clinical Calculations — Machine Learning of Hemodynamic Waveforms

Presenter: Steven Hsu

March 03, 2026

Presentation THT 2025

Prospective Validation of Machine Learning in Risk Stratification of Patients Treated for Cardiogenic Shock

Presenter: Shuojohn Li

February 11, 2025

Presentation THT 2024

Multicenter Development and Validation of a Supervised Machine Learning Risk Model to Predict Right Ventricular Failure Following Mechanical Circulatory Support: The STOP-RVF Score

Presenter: Stavros G. Drakos

March 06, 2024

News Features THT 2023

The Promise of AI for Improving Health Equity in Heart Failure

Todd Neale

April 04, 2023

Presentation THT 2022

Phenotyping Cardiogenic Shock: Insights From Machine Learning Applied to a Large Real-World Registry

Presenter: Navin Kapur

February 02, 2022

Advertisement

Cutaneous device and machine learning could estimate pulmonary capillary wedge pressure in patients with heart failure

UltraSight PVAD IQ Machine Learning Algorithm Accurately Identifies Impella Micro-axial Flow Pump Depth Across the Aortic Valve on Ultrasound Imaging: An Early Clinical Feasibility Study

Beyond Clinical Calculations — Machine Learning of Hemodynamic Waveforms

Prospective Validation of Machine Learning in Risk Stratification of Patients Treated for Cardiogenic Shock

Multicenter Development and Validation of a Supervised Machine Learning Risk Model to Predict Right Ventricular Failure Following Mechanical Circulatory Support: The STOP-RVF Score

The Promise of AI for Improving Health Equity in Heart Failure

Phenotyping Cardiogenic Shock: Insights From Machine Learning Applied to a Large Real-World Registry

Advertisement

Advertisement

Sign In

Forgot Your Password?

Search TCTMD

CME TITLE

Sign up for our newsletter

Search TCTMD

Submit an Event

Become a PREMIUM MEMBER or LOG IN to view exclusive content

REGISTER for free or LOG IN to view this content