Adoption of Transformer Neural Network to Improve the Diagnostic Performance of Oximetry for Obstructive Sleep Apnea

Scoring polysomnography for obstructive sleep apnea diagnosis is a laborious, long, and costly process. Machine learning approaches, such as deep neural networks, can reduce scoring time and costs. However, most methods require prior filtering and preprocessing of the raw signal. Our work presents a...

Descripción completa

Detalles Bibliográficos
Autores principales: Almarshad, Malak Abdullah, Al-Ahmadi, Saad, Islam, Md Saiful, BaHammam, Ahmed S., Soudani, Adel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536445/
https://www.ncbi.nlm.nih.gov/pubmed/37765980
http://dx.doi.org/10.3390/s23187924

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536445/
https://www.ncbi.nlm.nih.gov/pubmed/37765980
http://dx.doi.org/10.3390/s23187924

Ejemplares similares