AIMC Topic: Sleep

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Are pictures worth a thousand sleep signals?

Sleep Dec 11, 2023
Sleep Stages Sleep Polysomnography Deep Learning
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Standardized image-based polysomnography database and deep learning algorithm for sleep-stage classification.

Sleep Dec 11, 2023
STUDY OBJECTIVES: Polysomnography (PSG) scoring is labor-intensive, subjective, and often ambiguous. Recently several deep learning (DL) models for automated sleep scoring have been developed, they are tied to a fixed amount of input channels and res...
Algorithms Polysomnography Sleep Stages Deep Learning Sleep
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Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Oct 1, 2023
UNLABELLED: Since the publication of its 2020 position statement on artificial intelligence (AI) in sleep medicine by the American Academy of Sleep Medicine, there has been a tremendous expansion of AI-related software and hardware options for sleep ...
Humans United States Sleep Societies, Medical Software Artificial Intelligence Physicians
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A convolutional neural network-based decision support system for neonatal quiet sleep detection.

Mathematical biosciences and engineering : MBE Aug 29, 2023
Sleep plays an important role in neonatal brain and physical development, making its detection and characterization important for assessing early-stage development. In this study, we propose an automatic and computationally efficient algorithm to det...
China Child Infant, Newborn Sleep Stages Electroencephalography Sleep Humans Neural Networks, Computer Algorithms
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SleepSIM: Conditional GAN-based non-REM sleep EEG Signal Generator.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Synthetic data generation has become increasingly popular with the increasing use of generative networks. Recently, Generative Adversarial Network (GAN) architectures have produced exceptional results in synthetic image generation. However, time seri...
Sleep Computer Simulation Electroencephalography Medicine Neural Networks, Computer
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Scoring sleep with artificial intelligence enables quantification of sleep stage ambiguity: hypnodensity based on multiple expert scorers and auto-scoring.

Sleep Feb 8, 2023
STUDY OBJECTIVES: To quantify the amount of sleep stage ambiguity across expert scorers and to validate a new auto-scoring platform against sleep staging performed by multiple scorers.
Sleep Observer Variation Sleep Stages Artificial Intelligence Reproducibility of Results Humans
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A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jan 1, 2023
Sleep staging is crucial for diagnosing sleep-related disorders. The heavy and time-consuming task of manual staging can be released by automatic techniques. However, the automatic staging model would have a relatively poor performance when working o...
Neural Networks, Computer Learning Electroencephalography Sleep Sleep Stages Humans
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[Single-channel electroencephalogram signal used for sleep state recognition based on one-dimensional width kernel convolutional neural networks and long-short-term memory networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2022
Aiming at the problem that the unbalanced distribution of data in sleep electroencephalogram(EEG) signals and poor comfort in the process of polysomnography information collection will reduce the model's classification ability, this paper proposed a ...
Neural Networks, Computer Electroencephalography Algorithms Sleep
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An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation.

The Lancet. Digital health Dec 1, 2022
BACKGROUND: Electroencephalogram (EEG) monitoring is recommended as routine in newborn neurocritical care to facilitate early therapeutic decisions and outcome predictions. EEG's larger-scale implementation is, however, hindered by the shortage of ex...
Brain Infant, Newborn Humans Child Sleep Infant Monitoring, Physiologic Deep Learning Electroencephalography
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A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Recent years have shown a growth in the application of deep learning architectures such as convolutional neural networks (CNNs), to electrophysiology analysis. However, using neural networks with raw time-series data makes explainability a significan...
Sleep Neural Networks, Computer Sleep Stages
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