DeepSleep convolutional neural network allows accurate and fast detection of sleep arousal
Li and Guan present a deep learning approach for automatically segmenting sleep arousal regions based on polysomnographic recordings. The algorithm, which won an open competition, enables fast and accurate delineation of sleep arousal events and would be useful in the scoring process in clinical stu...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/7dc0c7b085f0446ebd7d82fc30ea81e1 |
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| Sumario: | Li and Guan present a deep learning approach for automatically segmenting sleep arousal regions based on polysomnographic recordings. The algorithm, which won an open competition, enables fast and accurate delineation of sleep arousal events and would be useful in the scoring process in clinical studies. |
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