MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model
Article
Article Title | MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model |
---|---|
ERA Journal ID | 5039 |
Article Category | Article |
Authors | Ji, Xiaopeng, Li, Yan, Wen, Peng, Barua, Prabal and Acharya, U Rajendra |
Journal Title | Computer Methods and Programs in Biomedicine |
Journal Citation | 244 |
Article Number | 107992 |
Number of Pages | 10 |
Year | 2024 |
Publisher | Elsevier |
Place of Publication | Ireland |
ISSN | 0169-2607 |
1872-7565 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.cmpb.2023.107992 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0169260723006582 |
Abstract | Background and Objective Methods Results Conclusion |
Keywords | 3D convolutional networks; graph convolutional networks; sleep stage classification |
Related Output | |
Is part of | Deep learning based sleep stage classification |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | This article is part of a UniSQ Thesis by publication. See Related Output. |
Byline Affiliations | School of Mathematics, Physics and Computing |
School of Engineering | |
Cogninet Australia, Australia |
https://research.usq.edu.au/item/z4y9v/mixsleepnet-a-multi-type-convolution-combined-sleep-stage-classification-model
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