aceIdentification of adventitious lung sounds in children with respiratory illnesses in Bangladesh using artificial intelligence and digital auscultation
Integrated management of childhood illness (IMCI) guidelines have high sensitivity but low specificity for pneumonia diagnosis. Artificial intelligence (AI)-enabled digital stethoscopes capable of analysing lung sounds may improve IMCI diagnostic performance. We evaluated the performance of an AI algorithm trained to identify normal and adventitious lung sounds in children. Non-physician health workers recorded lung sounds from four chest positions using a digital stethoscope in under-five-year-old children with…
Against a paediatrician panel, the AI algorithm detected abnormal lung sounds in under-five children with only about 62% sensitivity and 61% specificity, which limits its current usefulness for pneumonia diagnosis.
The algorithm only achieved moderate performance and could not categorise recordings as uninterpretable, so it needs more training before it could reliably support diagnosis.
Evidence
- Peer-reviewedScientific Reports2026-10-16
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Truvace Impact Record TRV-2026-1722, v1: “Identification of adventitious lung sounds in children with respiratory illnesses in Bangladesh using artificial intelligence and digital auscultation.” Truvace, 2026-10-17. /record/TRV-2026-1722 (accessed at citation time). sha256 ec7d7c5da7ede275…
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