Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis.

Journal: Journal of medical Internet research
PMID: 40249944

Abstract

BACKGROUND: Pediatric respiratory diseases, including asthma and pneumonia, are major causes of morbidity and mortality in children. Auscultation of lung sounds is a key diagnostic tool but is prone to subjective variability. The integration of artificial intelligence (AI) and machine learning (ML) with electronic stethoscopes offers a promising approach for automated and objective lung sound.

Authors

  • Ji Soo Park
    Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Sa-Yoon Park
    The Institute of Convergence Medicine with Innovative Technology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Jae Won Moon
    Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Kwangsoo Kim
    Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Dong In Suh
    Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea.

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