Cargando…
Comparison of deep transfer learning algorithms and transferability measures for wearable sleep staging
BACKGROUND: Obtaining medical data using wearable sensors is a potential replacement for in-hospital monitoring, but the lack of data for such sensors poses a challenge for development. One solution is using in-hospital recordings to boost performance via transfer learning. While there are many poss...
Autores principales: | Waters, Samuel H., Clifford, Gari D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465946/ https://www.ncbi.nlm.nih.gov/pubmed/36096868 http://dx.doi.org/10.1186/s12938-022-01033-3 |
Ejemplares similares
-
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
por: Radha, Mustafa, et al.
Publicado: (2021) -
A Deep Transfer Learning Framework for Sleep Stage Classification with Single-Channel EEG Signals
por: ElMoaqet, Hisham, et al.
Publicado: (2022) -
COVID-19 pneumonia level detection using deep learning algorithm and transfer learning
por: Ali, Abbas M., et al.
Publicado: (2022) -
A computationally efficient algorithm for wearable sleep staging in clinical populations
por: Fonseca, Pedro, et al.
Publicado: (2023) -
Towards Understanding Transfer Learning Algorithms Using Meta Transfer Features
por: Li, Xin-Chun, et al.
Publicado: (2020)