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

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.

Digital stethoscopes compared to standard auscultation for detecting abnormal paediatric breath sounds.

Unlabelled: Our study aimed to objectively describe the audiological characteristics of wheeze and crackles in children by using digital stethoscope (DS) auscultation, as well as assess concordance between standard auscultation and two different DS devices in their ability to detect pathological breath sounds. Twenty children were auscultated by a paediatric consultant doctor and digitally recorded using the Littman™ 3200 Digital Electronic Stethoscope and a Clinicloud™ DS with smart device. Using spectrographic analysis, we found those with clinically described wheeze had prominent periodic waveform segments spanning expiration for a period of 0.