2024
Automated Interpretation of Lung Sounds by Deep Learning in Children With Asthma: Scoping Review and Strengths, Weaknesses, Opportunities, and Threats Analysis
Ruchonnet-Métrailler I, Siebert J, Hartley M, Lacroix L. Automated Interpretation of Lung Sounds by Deep Learning in Children With Asthma: Scoping Review and Strengths, Weaknesses, Opportunities, and Threats Analysis. Journal Of Medical Internet Research 2024, 26: e53662. PMID: 39178033, PMCID: PMC11380063, DOI: 10.2196/53662.Peer-Reviewed Original ResearchConceptsGrey literature searchArtificial intelligenceScoping reviewPediatric asthmaLiterature searchManagement of pediatric asthmaField of medical AILung auscultationDeep learningMedical AIPersonalized management strategiesData collectionThreat analysisRemote monitoring capabilitiesInterpretation of lung soundsLung soundsAccuracy of AIData setsStandardized assessmentAutomated interpretationPulmonary auscultationAbsence of external validationEarly diagnosisIdentified strengthsLung sound analysis
2023
DeepBreath—automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries
Heitmann J, Glangetas A, Doenz J, Dervaux J, Shama D, Garcia D, Benissa M, Cantais A, Perez A, Müller D, Chavdarova T, Ruchonnet-Metrailler I, Siebert J, Lacroix L, Jaggi M, Gervaix A, Hartley M. DeepBreath—automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries. Npj Digital Medicine 2023, 6: 104. PMID: 37268730, PMCID: PMC10238513, DOI: 10.1038/s41746-023-00838-3.Peer-Reviewed Original ResearchAcute respiratory illnessPediatric outpatientsRespiratory illnessRespiratory pathologyLung auscultationReceiver operator characteristicHealthy controlsRespiratory rateThoracic sitesRespiratory cycleBronchiolitisPneumoniaOutpatientsPatientsPathological breathingIllnessPathologyAuscultationDisordersSignificant improvementObjective estimatesBreathingAUROC