Automated Detection of Aortic Stenosis Using Machine Learning.

Journal: Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Published Date: Jan 11, 2023

Abstract

BACKGROUND: Aortic stenosis (AS) is a degenerative valve condition that is underdiagnosed and undertreated. Detection of AS using limited two-dimensional echocardiography could enable screening and improve appropriate referral and treatment of this condition. The aim of this study was to develop methods for automated detection of AS from limited imaging data sets.

Authors

  • Benjamin S Wessler
    CardioVascular Center, Tufts Medical Center, Boston, Massachusetts. Electronic address: bwessler@tuftsmedicalcenter.org.
  • Zhe Huang
  • Gary M Long
    CVAI Solutions, Dorchester, Massachusetts.
  • Stefano Pacifici
    Department of Medicine, Tufts Medical Center, Boston, Massachusetts.
  • Nishant Prashar
    Department of Medicine, Tufts Medical Center, Boston, Massachusetts.
  • Samuel Karmiy
    Department of Medicine, Tufts Medical Center, Boston, Massachusetts.
  • Roman A Sandler
    iCardio.ai, Los Angeles, California.
  • Joseph Z Sokol
    iCardio.ai, Los Angeles, California.
  • Daniel B Sokol
    iCardio.ai, Los Angeles, California.
  • Monica M Dehn
    CardioVascular Center, Tufts Medical Center, Boston, Massachusetts.
  • Luisa Maslon
    CardioVascular Center, Tufts Medical Center, Boston, Massachusetts.
  • Eileen Mai
    CardioVascular Center, Tufts Medical Center, Boston, Massachusetts.
  • Ayan R Patel
    CardioVascular Center, Tufts Medical Center, Boston, Massachusetts.
  • Michael C Hughes
    Department of Computer Science, Tufts University, 161 College Ave, Medford, MA, 02155, USA.

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