Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes.

Journal: Respiratory research

Published Date: Sep 29, 2020

Abstract

BACKGROUND: Manual auscultation to detect abnormal breath sounds has poor inter-observer reliability. Digital stethoscopes with artificial intelligence (AI) could improve reliable detection of these sounds. We aimed to independently test the abilities of AI developed for this purpose.

Authors

Ajay Kevat

Department of Paediatrics, Monash University, Melbourne, Australia. ajaykevat@gmail.com.
Anaath Kalirajah

Department of Paediatrics, Monash University, Melbourne, Australia.
Robert Roseby

Department of Paediatrics, Monash University, Melbourne, Australia.

Keywords

Artificial Intelligence Auscultation Child Child, Preschool Female Humans Male Reproducibility of Results Respiratory Sounds Stethoscopes

External Resources

View on PubMed Access via DOI PubMed (32993620)

Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes.

Abstract

Authors

Keywords

External Resources

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