DeepBreath—automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpatients to develop DeepBreath : a deep learni...

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Detalles Bibliográficos
Autores principales: Heitmann, Julien, Glangetas, Alban, Doenz, Jonathan, Dervaux, Juliane, Shama, Deeksha M., Garcia, Daniel Hinjos, Benissa, Mohamed Rida, Cantais, Aymeric, Perez, Alexandre, Müller, Daniel, Chavdarova, Tatjana, Ruchonnet-Metrailler, Isabelle, Siebert, Johan N., Lacroix, Laurence, Jaggi, Martin, Gervaix, Alain, Hartley, Mary-Anne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238513/
https://www.ncbi.nlm.nih.gov/pubmed/37268730
http://dx.doi.org/10.1038/s41746-023-00838-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238513/
https://www.ncbi.nlm.nih.gov/pubmed/37268730
http://dx.doi.org/10.1038/s41746-023-00838-3

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