Machine Learning Methods to Predicting Transvalvular Gradient Waveform Post-Transcatheter Aortic Valve Replacement Using Pre-procedural Echocardiogram.

Journal: The Journal of thoracic and cardiovascular surgery
Published Date: May 2, 2025

Abstract

OBJECTIVE: Time-varying transvalvular pressure gradient after transcatheter aortic valve replacement indicates the effectiveness of the therapy. The objective was to develop a novel machine learning method enhanced by generative artificial intelligence and smart data selection strategies to predict the post-transcatheter aortic valve replacement gradient waveform using pre-procedural Doppler echocardiogram.

Authors

  • Wenyuan Song
    School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA USA; Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA USA.
  • Taylor Sirset-Becker
    Department of Biomedical Sciences, The Ohio State University College of Medicine, Columbus, OH USA.
  • Luis RenĂ© Mata Quinonez
    Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA USA.
  • Dhruv Polsani
    Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA USA.
  • Venkateshwar Polsani
    Department of Cardiac Surgery, Piedmont Heart Institute, Atlanta, Ga.
  • Pradeep Yadav
    Department of Cardiac Surgery, Piedmont Heart Institute, Atlanta, Ga.
  • Vinod Thourani
    Department of Cardiac Surgery, Piedmont Heart Institute, Atlanta, GA USA.
  • Lakshmi Prasad Dasi
    Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Ga.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals