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. METHODS:One hundred and ninety two auscultation recordings collected from children using two different digital stethoscopes (Clinicloud™ and Littman™) were each tagged as containing wheezes, crackles or neither by a pediatric respiratory physician, based on audio playback and careful spectrogram and waveform analysis, with a subset validated by a blinded second clinician. These recordings were submitted for analysis by a blinded AI algorithm (StethoMe AI) specifically trained to detect pathologic pediatric breath sounds. RESULTS:With optimized AI detection thresholds, crackle detection positive percent agreement (PPA) was 0.95 and negative percent agreement (NPA) was 0.99 for Clinicloud recordings; for Littman-collected sounds PPA was 0.82 and NPA was 0.96. Wheeze detection PPA and NPA were 0.90 and 0.97 respectively (Clinicloud auscultation), with PPA 0.80 and NPA 0.95 for Littman recordings. CONCLUSIONS:AI can detect crackles and wheeze with a reasonably high degree of accuracy from breath sounds obtained from different digital stethoscope devices, although some device-dependent differences do exist.
journal_name
Respir Resjournal_title
Respiratory researchauthors
Kevat A,Kalirajah A,Roseby Rdoi
10.1186/s12931-020-01523-9subject
Has Abstractpub_date
2020-09-29 00:00:00pages
253issue
1eissn
1465-9921issn
1465-993Xpii
10.1186/s12931-020-01523-9journal_volume
21pub_type
杂志文章abstract:BACKGROUND:The investigation of mesenchymal stromal cell (MSC)-conditioned medium or extracellular vesicles (exosomes or microvesicles) as a remedy for acute lung injury (ALI) or acute respiratory distress syndrome (ARDS) has become a fast-growing field in recent years. Our purpose was to conduct a meta-analysis to inv...
journal_title:Respiratory research
pub_type: 杂志文章
doi:10.1186/s12931-020-01574-y
更新日期:2020-11-20 00:00:00
abstract::Mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) is a protein with anti-inflammatory properties and the archetypal member of the dual-specificity phosphatases (DUSPs) family that have emerged over the past decade as playing an instrumental role in the regulation of airway inflammation. Not only does MKP-1...
journal_title:Respiratory research
pub_type: 杂志文章,评审
doi:10.1186/s12931-017-0637-3
更新日期:2017-08-10 00:00:00
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journal_title:Respiratory research
pub_type: 杂志文章
doi:10.1186/1465-9921-8-23
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abstract:BACKGROUND:Tracheal epithelial cells are anchored to a dynamic basement membrane that contains a variety of extracellular matrix proteins including collagens and laminins. During development, wound repair and disease of the airway epithelium, significant changes in extracellular matrix proteins may directly affect cell...
journal_title:Respiratory research
pub_type: 杂志文章
doi:10.1186/1465-9921-7-105
更新日期:2006-08-02 00:00:00
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journal_title:Respiratory research
pub_type: 临床试验,杂志文章
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journal_title:Respiratory research
pub_type: 杂志文章
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journal_title:Respiratory research
pub_type: 杂志文章,meta分析,评审
doi:10.1186/1465-9921-5-17
更新日期:2004-10-27 00:00:00
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journal_title:Respiratory research
pub_type: 杂志文章,评审
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更新日期:2018-08-06 00:00:00
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journal_title:Respiratory research
pub_type: 杂志文章
doi:10.1186/1465-9921-12-147
更新日期:2011-11-06 00:00:00
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pub_type: 杂志文章
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doi:10.1186/s12931-018-0927-4
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journal_title:Respiratory research
pub_type: 杂志文章
doi:10.1186/s12931-016-0464-y
更新日期:2016-11-14 00:00:00
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journal_title:Respiratory research
pub_type: 杂志文章
doi:10.1186/1465-9921-14-118
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doi:10.1186/s12931-019-1260-2
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pub_type: 杂志文章
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pub_type: 杂志文章
doi:10.1186/s12931-020-01442-9
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journal_title:Respiratory research
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pub_type: 杂志文章
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journal_title:Respiratory research
pub_type: 杂志文章
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pub_type: 杂志文章
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abstract:: ...
journal_title:Respiratory research
pub_type: 社论
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更新日期:2018-11-26 00:00:00
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pub_type: 杂志文章
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更新日期:2017-05-08 00:00:00