Automated Interpretation of Lung Sounds by Deep Learning in Children With Asthma: Scoping Review and Strengths, Weaknesses, Opportunities, and Threats Analysis.

Journal: Journal of medical Internet research
PMID: 39178033

Abstract

BACKGROUND: The interpretation of lung sounds plays a crucial role in the appropriate diagnosis and management of pediatric asthma. Applying artificial intelligence (AI) to this task has the potential to better standardize assessment and may even improve its predictive potential.

Authors

  • Isabelle Ruchonnet-Métrailler
    Pediatric Pulmonology Unit, Department of Pediatrics, Geneva Children's Hospital, University Hospitals of Geneva, Geneva, Switzerland.
  • Johan N Siebert
    Division of Paediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals, 47 Avenue de la Roseraie, 1205, Geneva, Switzerland. Johan.Siebert@hcuge.ch.
  • Mary-Anne Hartley
    Intelligent Global Health, Machine Learning and Optimization (MLO) Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Laurence Lacroix
    Faculty of Medicine, University of Geneva, Geneva, Switzerland.

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