GI-SleepNet: A Highly Versatile Image-Based Sleep Classification Using a Deep Learning Algorithm

Sleep-stage classification is essential for sleep research. Various automatic judgment programs, including deep learning algorithms using artificial intelligence (AI), have been developed, but have limitations with regard to data format compatibility, human interpretability, cost, and technical requ...

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Detalles Bibliográficos
Autores principales: Gao, Tianxiang, Li, Jiayi, Watanabe, Yuji, Hung, Chijung, Yamanaka, Akihiro, Horie, Kazumasa, Yanagisawa, Masashi, Ohsawa, Masahiro, Kume, Kazuhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628800/
https://www.ncbi.nlm.nih.gov/pubmed/34842647
http://dx.doi.org/10.3390/clockssleep3040041

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628800/
https://www.ncbi.nlm.nih.gov/pubmed/34842647
http://dx.doi.org/10.3390/clockssleep3040041

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