Multi-Stage Respiratory Sound Analysis: Confidence-Driven Wheeze & Crackle Detection

This framework advances computer-aided respiratory diagnostics, improving early detection and monitoring of pediatric respiratory conditions. By integrating expert-inspired segmentation with machine learning-driven confidence estimation, it has potential to enhance clinical workflows and screening for pulmonary diseases, particularly in resource-limited settings.

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Publication Details

Journal
IEEE Transactions on Biomedical Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tbme.2025.3613489
Primary Topic
Phonocardiography and Auscultation Techniques
Type
article
Field-Weighted Citation Impact
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article

Multi-Stage Respiratory Sound Analysis: Confidence-Driven Wheeze & Crackle Detection

Annapurna Kala, Mounya Elhilali
IEEE Transactions on Biomedical Engineering
Phonocardiography and Auscultation Techniques
article

Multi-Stage Respiratory Sound Analysis: Confidence-Driven Wheeze & Crackle Detection

Annapurna Kala, Mounya Elhilali
article en

Abstract

This framework advances computer-aided respiratory diagnostics, improving early detection and monitoring of pediatric respiratory conditions. By integrating expert-inspired segmentation with machine learning-driven confidence estimation, it has potential to enhance clinical workflows and screening for pulmonary diseases, particularly in resource-limited settings.

IEEE Transactions on Biomedical EngineeringVol. PP
Johns Hopkins University (US)
Openalex Percentile: Top 63%
Phonocardiography and Auscultation Techniques
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