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DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries.
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.
Afiliación
  • Heitmann J; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Glangetas A; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Doenz J; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Dervaux J; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Shama DM; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Garcia DH; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Benissa MR; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Cantais A; Pediatric Emergency Department, Hospital University of Saint Etienne, Saint Etienne, France.
  • Perez A; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Müller D; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Chavdarova T; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Ruchonnet-Metrailler I; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Siebert JN; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Lacroix L; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Jaggi M; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
  • Gervaix A; Division of Pediatric Emergency Medicine, Department of Women, Child and Adolescent, Geneva University Hospitals (HUG), University of Geneva, Switzerland, Geneva, Switzerland.
  • Hartley MA; Intelligent Global Health Research Group, Machine Learning and Optimization Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. mary-anne.hartley@epfl.ch.
NPJ Digit Med ; 6(1): 104, 2023 Jun 02.
Article en En | MEDLINE | ID: mdl-37268730
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: NPJ Digit Med Año: 2023 Tipo del documento: Article País de afiliación: Suiza
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: NPJ Digit Med Año: 2023 Tipo del documento: Article País de afiliación: Suiza