Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data

The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of chronic diseases, 75 of non-chronic diseases and only 35 of heal...

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Detalles Bibliográficos
Autores principales: García-Ordás, María Teresa, Benítez-Andrades, José Alberto, García-Rodríguez, Isaías, Benavides, Carmen, Alaiz-Moretón, Héctor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070339/
https://www.ncbi.nlm.nih.gov/pubmed/32098446
http://dx.doi.org/10.3390/s20041214

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070339/
https://www.ncbi.nlm.nih.gov/pubmed/32098446
http://dx.doi.org/10.3390/s20041214

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