Towards automatic diagnosis of rheumatic heart disease on echocardiographic exams through video-based deep learning.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Aug 13, 2021

Abstract

OBJECTIVE: Rheumatic heart disease (RHD) affects an estimated 39 million people worldwide and is the most common acquired heart disease in children and young adults. Echocardiograms are the gold standard for diagnosis of RHD, but there is a shortage of skilled experts to allow widespread screenings for early detection and prevention of the disease progress. We propose an automated RHD diagnosis system that can help bridge this gap.

Authors

  • João Francisco B S Martins
    Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
  • Erickson R Nascimento
    Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
  • Bruno R Nascimento
    Cardiology Service and Telehealth Center, Hospital das Clínicas, and Department of Internal Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
  • Craig A Sable
    Children's National Medical Center, Washington, DC, USA.
  • Andrea Z Beaton
    Cincinnati Children's Hospital Medical Center, The Heart Institute, Cincinnati, Ohio, USA.
  • Antônio L Ribeiro
    Cardiology Service and Telehealth Center, Hospital das Clínicas, and Department of Internal Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
  • Wagner Meira
    Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Gisele L Pappa
    Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

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