Deep Learning in Sleep Medicine: Advantages and Drawbacks
Abstract
Considering the advancements in machine learning, neural networks (NNs), as models of the human brain with the ability of generalization, have gained a great deal of attention in numerous fields of science such as sleep medicine for years (1). NNs have been widely used in sleep apnea detection, sleep stage recognition, audio-based snore detection, insomnia identification, detecting sleep-related movement disorder (SRMD), etc.
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2.Haghayegh S, Khoshnevis S, Smolensky MH, et al. Application of deep learning to improve sleep scoring of wrist actigraphy. Sleep Med 2020; 74: 235-41.
3.Civaner OF, Kamaşak M. Classification of pediatric snoring episodes using deep convolutional neural net-works. 2018 p. 1-4.
4.Mortaza ZS. Nonlinear electroencephalogram (EEG)analysis in sleep medicine. J Sleep Sci 2021; 5: 122-3.
5.Sharma DK, Tokas B, Adlakha L. Deep learning in big data and data mining. In: Piuri V, Raj S, GenoveseA, Srivastava R, editors. trends in deep learning methodologies hybrid computational intelligence for pattern analysis. Cambridge, MA: Academic Press;2021. p. 37-61.
6.Franca RP, Borges Monteiro AC, Arthur R, et al. An overview of deep learning in big data, image, and signal processing in the modern digital age. In: Piuri V,Raj S, Genovese A, Srivastava R, editors. Trends in deep learning methodologies hybrid computational intelligence for pattern analysis. Cambridge, MA: Academic Press; 2021. p. 63-87.
7.Ismail Fawaz H, Forestier G, Weber J, et al. Deep learning for time series classification: A review. Data Min Knowl Discov 2019; 33: 917-63.
8.Liu F, Rosenberger J, Lou Y, et al. Graph Regularized EEG Source Imaging with In-Class Consistency and Out-Class Discrimination. IEEE Trans Big Data2017; 3: 378-91.
9.Chaovalitwongse WA, Chou CA, Liang Z, et al. Applied optimization and data mining. Ann Oper Res2017; 249: 1-3.
| Files | ||
| Issue | Vol 6 No 1-2 (2021): Winter-Spring | |
| Section | Letter to Editor | |
| DOI | https://doi.org/10.18502/jss.v6i(1-2).9295 | |
| Keywords | ||
| Deep Learning Sleep Medicine Machine Learning Artificial Intelligence | ||
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Zangeneh Soroush M. Deep Learning in Sleep Medicine: Advantages and Drawbacks. J Sleep Sci. 2022;6(1-2):51-52.
