Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention

This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote monitoring through the development of a real-time wheeze counting algorithm. Leveraging a novel approach that includes the detailed labeling of one breathing cycle into three types: break, normal, and w...

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Detalles Bibliográficos
Autores principales: Im, Sunghoon, Kim, Taewi, Min, Choongki, Kang, Sanghun, Roh, Yeonwook, Kim, Changhwan, Kim, Minho, Kim, Seung Hyun, Shim, KyungMin, Koh, Je-sung, Han, Seungyong, Lee, JaeWang, Kim, Dohyeong, Kang, Daeshik, Seo, SungChul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659186/
https://www.ncbi.nlm.nih.gov/pubmed/37983213
http://dx.doi.org/10.1371/journal.pone.0294447

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659186/
https://www.ncbi.nlm.nih.gov/pubmed/37983213
http://dx.doi.org/10.1371/journal.pone.0294447

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