Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography.

Journal: Pediatric cardiology
Published Date: Oct 8, 2022

Abstract

BACKGROUND: Left ventricular (LV) volumes, ejection fraction (EF), and myocardial strain have been shown to be predictive of clinical and subclinical heart disease. Automation of LV functional assessment overcomes difficult technical challenges and complexities. We sought to assess whether a fully automated assessment of LV function could be reliably used in children and young adults.

Authors

  • Ling Li
    College of Communication Engineering, Jilin University, Changchun, Jilin China.
  • Paul Homer
    Department of Pediatric Cardiology, University of Nebraska College of Medicine and Children's Hospital and Medical Center Omaha, Omaha, NE, USA.
  • Mary Craft
    Department of Pediatric Cardiology, University of Nebraska College of Medicine and Children's Hospital and Medical Center Omaha, Omaha, NE, USA.
  • Shelby Kutty
    Department of Pediatrics, at Johns Hopkins School of Medicine, Baltimore, MD, 21287, USA.
  • Adam Putschoegl
    Department of Pediatric Cardiology, University of Nebraska College of Medicine and Children's Hospital and Medical Center Omaha, Omaha, NE, USA.
  • Amanda Marshall
    Department of Pediatric Cardiology, University of Nebraska College of Medicine and Children's Hospital and Medical Center Omaha, Omaha, NE, USA.
  • David Danford
    Department of Pediatric Cardiology, University of Nebraska College of Medicine and Children's Hospital and Medical Center Omaha, Omaha, NE, USA.
  • Anji Yetman
    Department of Pediatric Cardiology, University of Nebraska College of Medicine and Children's Hospital and Medical Center Omaha, Omaha, NE, USA.

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